An official website of the United States government
Magnetic Field Assisted Additive Manufacturing (MFAAM), 3D printing in a magnetic field, has the potential to fabricate high magnetic strength anisotropic bonded magnets. Here, 10, 35, and 54 wt% strontium ferrite bonded magnets using polyamide 12 binder were developed by twin screw compounding process and then printed via MFAAM samples in zero, and in 0.5 Tesla (H parallel to the print direction and print bed). The hysteresis curves were measured using a MicroSense EZ9 Vibrating Sample Magnetometer (VSM) for 3 different mount orientations of the sample on the sample holder to explore the magnetic anisotropy. The samples printed in zero field exhibited a weak anisotropy with an easy axis perpendicular to the print direction. This anisotropy is caused by the effect of shear flow on the orientation of the magnetic platelets in the 3D printer head. For the MFAAM samples, the S values are largest along the print bed normal. This anisotropy is caused by the field. The alignment of the magnetic particles happens when the molten suspension is in the extruder. When the material is printed, it is folded over on the print bed and its easy axis rotates 90° parallel to the print bed normally. Little realignment of the particles happens after it is printed, suggesting a sharp drop in temperature once the composite touches the print bed, indicating that field-induced effects in the nozzle dominate the anisotropy of MFAAM deposited samples.
more »
« less
Measurement and Analysis of Pressure Profile Within Big Area Additive Manufacturing Single Screw Extruder.
Pressure distributions within a single screw extruder are dependent on several factors, namely, processing parameters and flow geometry. The Big Area Additive Manufacturing (BAAM) system involves a complex flow geometry with multiple flow zones following the screw extruder. This study utilized experimental data and a one-dimensional (1-D) analytical model to compare pressures at specific areas of interest in the BAAM system. Initial results show a need for further two-dimensional (2-D) and three-dimensional (3-D) simulation and modeling of the BAAM extruder with more accurate underlying assumptions. The results of this work will allow for further study of BAAM input parameters for optimal print quality, material properties, and print head geometric design.
more »
« less
- Award ID(s):
- 1841507
- PAR ID:
- 10200739
- Date Published:
- Journal Name:
- Solid Freeform Fabrication Symposium proceedings
- ISSN:
- 1053-2153
- Page Range / eLocation ID:
- 1242-1250
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
The development of new thermoplastic-based nanocomposites for, as well as using, 3D printing requires extensive experimental testing. One typically goes through many failed, or otherwise sub-optimal, iterations before finding acceptable solutions (e.g. compositions, 3D printing parameters). It is desirable to reduce the number of such iterations as well as exclude failed experiments that often require laborious disassembly and cleaning of the 3D printer. This issue could be addressed if we were able to understand, and ultimately predict ahead of experiments if a given material can be 3D printed successfully. Herein, we report on our investigations into forecasting the printing and resultant properties of polymer nanocomposites while encompassing both material properties and printing parameters, enabling the model to generalize across various thermoplastics and additives. To do so, nanocomposites of two different commercially available bio-based PLAs with varying concentrations of nanoclay (NC) and graphene nanoplatelets (GNP) were prepared using a twin-screw extruder. The thermal and rheological properties of the nanocomposites were analyzed. These materials were printed at varying temperature and flow using a pellet printer. The quality of the printing was evaluated by measuring weight fluctuation, internal diameter of cylindrical specimen, and surface uniformity. The interactions between material properties and printing parameters are complex but captured effectively by a machine learning model, specifically we demonstrate such a predictive model to forecast printability and, printing quality utilizing a Random Forest algorithm. Printability was predicted by developing a classification model with constraints based on the weight fluctuation (W ) of the printed sample w.r.t. the optimal print; defining ‘‘not printable’’ for −1.0 d W < −0.8 and ‘‘printable’’ for W e −0.8. The classification model for predicting printability, performed well with an accuracy of 92.8% and identified flow index and complex viscosity, contributing 52% to the model’s importance. Another model to predict W of the only on successful prints also showed strong performance, emphasizing the importance of viscoelastic properties, thermal stability, and printing temperature. For diameter change (Di), the Random Forest model identified flow consistency index, complex viscosity, and thermal stability as influential parameters, with crystallization enthalpy gaining increased importance, reflecting its role in crystallization and shrinkage. In contrast, the surface roughness average (RA) model had lower performance, yet revealed remarkable insights regarding the feature importance with crystallization enthalpy and complex viscosity being most significant.more » « less
-
The X-cube model, a prototypical gapped fracton model, was shown in Ref. [1] to have a foliation structure. That is, inside the 3+1 D model, there are hidden layers of 2+1 D gapped topological states. A screw dislocation in a 3+1 D lattice can often reveal nontrivial features associated with a layered structure. In this paper, we study the X-cube model on lattices with screw dislocations. In particular, we find that a screw dislocation results in a finite change in the logarithm of the ground state degeneracy of the model. Part of the change can be traced back to the effect of screw dislocations in a simple stack of 2+1 D topological states, hence corroborating the foliation structure in the model. The other part of the change comes from the induced motion of fractons or sub-dimensional excitations along the dislocation, a feature absent in the stack of 2+1D layers.more » « less
-
Pneumatic micro-extrusion (PME) presents inherent challenges in achieving precise control over material deposition due to the small scale and high viscosity of the material flow. Traditional experimental methods often fall short in capturing the complex mechanisms, interactions, and dynamics governing material transport and deposition in PME, highlighting the necessity for advanced computational approaches to unveil these intricate physical phenomena. The primary objective of this study is to develop a robust computational framework for simulating material transport and deposition in PME, offering detailed insights into the fluid dynamics, flow complexities, and deposition characteristics intrinsic to the PME process. This involves systematically investigating the influence of key process parameters, such as material properties, print speed, and flow pressure, on deposition dynamics. Three-dimensional (3D) computational fluid dynamics (CFD) modeling was employed using ANSYS Fluent, with boundary conditions defined to replicate pneumatic extrusion on a moving substrate. The CFD simulations captured three distinct deposition regimes: (i) under-extrusion, (ii) normal extrusion, and (iii) over-extrusion. Results show that decreasing print speed at constant inlet velocity produced over-extrusion, with increased bead height and width due to material overflow. At normal extrusion, bead geometry remained stable, while under-extrusion reduced bead width and ultimately led to discontinuities when flow stresses exceeded cohesive strength. Notably, bead width decreased significantly between 10 mm/s and 15 mm/s, but showed little difference between 15 mm/s and 20 mm/s. Instead, the higher speed produced discontinuities consistent with experimental observations. Centerline velocity profiles revealed that the flow inside the cartridge was very slow at approximately 0.058 mm/s, whereas the velocity increased sharply within the nozzle throat, reaching nearly 12.88 mm/s. These predictions were further supported by validation experiments, where the measured nozzle velocity of 12.95 mm/s closely matched the CFD-simulated value of 12.88 mm/s, demonstrating strong agreement between simulation and experiment. Additionally, pressure decreased slightly with increasing print speed due to reduced backflow, while nozzle velocity and wall shear stress remained unchanged under fixed inlet velocity conditions. Overall, the outcomes of this study are expected to inform parameter optimization strategies and enhance PME process efficiency, providing critical insights into how variations in PME process dynamics influence print morphology and quality, advancing the path toward optimized fabrication of scaffolds for tissue engineering applications.more » « less
-
Gas-dynamic virtual nozzles (GDVNs) play a vital role in delivering biomolecular samples during diffraction measurements at X-ray free-electron laser facilities. Recently, submicrometer resolution capabilities of two-photon polymerization 3D printing techniques opened the possibility to quickly fabricate gas-dynamic virtual nozzles with practically any geometry. In our previous work, we exploited this capability to print asymmetric gas-dynamic virtual nozzles that outperformed conventional symmetric designs, which naturally leads to the question of how to identify the optimal gas-dynamic virtual nozzle geometry. In this work, we develop a 3D computational fluid dynamics pipeline to investigate how the characteristics of microjets are affected by gas-dynamic virtual nozzle geometry, which will allow for further geometry optimizations and explorations. We used open-source software (OpenFOAM) and an efficient geometric volume-of-fluid method ( isoAdvector ) to affordably and accurately predict jet properties for different nozzle geometries. Computational resources were minimized by utilizing adaptive mesh refinement. The numerical simulation results showed acceptable agreement with the experimental data, with a relative error of about 10% for our test cases that compared bell- and cone-shaped sheath-gas cavities. In these test cases, we used a relatively low sheath gas flow rate (6 mg/min), but future work including the implementation of compressible flows will enable the investigation of higher flow rates and the study of asymmetric drip-to-jet transitions.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- The DOI is not currently available.
