skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.
Attention:The NSF Public Access Repository (NSF-PAR) system and access will be unavailable from 7:00 AM ET to 7:30 AM ET on Friday, April 24 due to maintenance. We apologize for the inconvenience.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


  • NSF Public Access
  • Search Results
  • Design of Shape Forming Elements for Architected Composites via Bayesian Optimization and Genetic Algorithms: A Concept Evaluation
Title: Design of Shape Forming Elements for Architected Composites via Bayesian Optimization and Genetic Algorithms: A Concept Evaluation
This article presents the first use of shape forming elements (SFEs) to produce architected composites from multiple materials in an extrusion process. Each SFE contains a matrix of flow channels connecting input and output ports, where materials are routed between corresponding ports. The mathematical operations of rotation and shifting are described, and design automation is explored using Bayesian optimization and genetic algorithms to select fifty or more parameters for minimizing two objective functions. The first objective aims to match a target cross-section by minimizing the pixel-by-pixel error, which is weighted with the structural similarity index (SSIM). The second objective seeks to maximize information content by minimizing the SSIM relative to a white image. Satisfactory designs are achieved with better objective function values observed in rectangular rather than square flow channels. Validation extrusion of modeling clay demonstrates that while SFEs impose complex material transformations, they do not achieve the material distributions predicted by the digital model. Using the SSIM for results comparison, initial stages yielded SSIM values near 0.8 between design and simulation, indicating a good initial match. However, the control of material processing tended to decline with successive SFE processing with the SSIM of the extruded output dropping to 0.023 relative to the design intent. Flow simulations more closely replicated the observed structures with SSIM values around 0.4 but also failed to predict the intended cross-sections. The evaluation highlights the need for advanced modeling techniques to enhance the predictive accuracy and functionality of SFEs for biomedical, energy storage, and structural applications.  more » « less
Award ID(s):
2118808 2119040
PAR ID:
10555236
Author(s) / Creator(s):
; ; ;
Publisher / Repository:
NSF PAR
Date Published:
Journal Name:
Materials
Volume:
17
Issue:
21
ISSN:
1996-1944
Page Range / eLocation ID:
5339
Subject(s) / Keyword(s):
architected composites additive manufacturing artificial intelligence optimization
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; (, Additive manufacturing)
    null (Ed.)
    Compressibility and viscosity of polymer feedstock are critical to their volumetric flow rate, weld strength, and dimensional accuracy in material extrusion additive manufacturing. In this work, the compressibility and viscosity of an acrylonitrile butadiene styrene (ABS) material is characterized with an instrumented hot end design. Experiments are first performed with a blocked nozzle to characterize the compressibility behavior. The results closely emulate the pressure-volume-temperature (PVT) behavior of a characterized generic ABS. Experiments are then performed with an open nozzle over a range of volumetric flow rates and temperatures. The static pressure data is fit to power-law, Ellis, and Cross viscosity models and the dynamic melt pressure data is then used to jointly fit material constitutive models for compressibility and viscosity. The results suggest that the joint fitting substantially improves the fidelity relative to the separately characterized viscosity and compressibility. The implemented methods support material extrusion process simulation and control including real-time identification of process faults such as (1) limited melting capacity of the hot end, (2) skipping (grinding) of the extruder drive gears, (3) low initial nozzle temperature, (4) varying flow rates associated with the intermeshing gear tooth velocity profile, and (5) delays and reduced melt pressures due to drool prior to extrusion. The ability to monitor the printing process for faults in real time, such as that presented in this work, is critical to born qualified parts. Additionally, these approaches can be used to screen new materials and identify optimal processing conditions that avoid these process faults. 
    more » « less
  2. ; ; ; ; ; (, Monthly Notices of the Royal Astronomical Society)
    Abstract Measurements of the star formation efficiency (SFE) of giant molecular clouds (GMCs) in the Milky Way generally show a large scatter, which could be intrinsic or observational. We use magnetohydrodynamic simulations of GMCs (including feedback) to forward-model the relationship between the true GMC SFE and observational proxies. We show that individual GMCs trace broad ranges of observed SFE throughout collapse, star formation, and disruption. Low measured SFEs ($${\ll} 1\hbox{ per cent}$$) are ‘real’ but correspond to early stages; the true ‘per-freefall’ SFE where most stars actually form can be much larger. Very high ($${\gg} 10\hbox{ per cent}$$) values are often artificially enhanced by rapid gas dispersal. Simulations including stellar feedback reproduce observed GMC-scale SFEs, but simulations without feedback produce 20× larger SFEs. Radiative feedback dominates among mechanisms simulated. An anticorrelation of SFE with cloud mass is shown to be an observational artefact. We also explore individual dense ‘clumps’ within GMCs and show that (with feedback) their bulk properties agree well with observations. Predicted SFEs within the dense clumps are ∼2× larger than observed, possibly indicating physics other than feedback from massive (main-sequence) stars is needed to regulate their collapse. 
    more » « less
  3. ; ; ; ; ; (, Proceedings of the ASME Conference on Smart Materials, Adaptive Structures, and Intelligent Systems)
    Robotic Materials are materials that have sensing, computation and, possibly actuation, distributed throughout the bulk of the material. In such a material, we envision semiconducting polymer based sensing, actuation, and information processing for on-board decision making to be designed, in tandem, with the smart product that will be implemented with the smart material. Prior work in printing polymer semiconductors for sensing and cognition have focused on highly energetic inkjet printing. Alternatively, we are developing liquid polymer extrusion processes to work hand-in-hand with existing solid polymer extrusion processes (such as Fused Deposition Manufacturing - FDM) to simultaneously deposit sensing, computation, actuation and structure. We demonstrate the successful extrusion printing of conductors and capacitors to impedance-match a new, higher-performance organic transistor design that solves the cascading problem of the device previously reported and is more amenable to liquid extrusion printing. Consequently, these printed devices are integrated into a sheet material that is folded into a 3-D, six-legged walking machine with attached electric motor. 
    more » « less
  4. ; ; ; ; ; ; ; ; (, International Journal of Plasticity)
    Multi-principal-element alloys (MPEAs) based on 3d-transition metals show remarkable mechanical properties. The stacking fault energy (SFE) in face-centered cubic (fcc) alloys is a critical property that controls underlying deformation mechanisms and mechanical response. Here, we present an exhaustive density-functional theory study on refractory- and copper-reinforced Cantor-based systems to ascertain the effects of refractory metal chemistry on SFE. We find that even a small percent change in refractory metal composition significantly changes SFEs, which correlates favorably with features like electronegativity variance, size effect, and heat of fusion. For fcc MPEAs, we also detail the changes in mechanical properties, such as bulk, Young’s, and shear moduli, as well as yield strength. A Labusch-type solute-solution-strengthening model was used to evaluate the temperature-dependent yield strength, which, combined with SFE, provides a design guide for high-performance alloys. We also analyzed the electronic structures of two down-selected alloys to reveal the underlying origin of optimal SFE and strength range in refractory-reinforced fcc MPEAs. These new insights on tuning SFEs and modifying composition-structure-property correlation in refractory- and copper-reinforced MPEAs by chemical disorder, provide a chemical route to tune twinning- and transformation-induced plasticity behavior. 
    more » « less
  5. ; ; ; ; ; ; (, Polymer Engineering & Science)
    Abstract This study aims to establish a systematic approach for characterizing recycled polyolefins of unknown composition, with a specific focus on predicting their performance in film extrusion. We explore various characterization techniques, including differential scanning calorimetry (DSC), Fourier‐transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), and rheometry to assess their effectiveness in identifying the polyethylene (PE) fractions within polypropylene (PP) recyclates. By integrating experimental data with modeling techniques, we aim to provide insights into the predictive capabilities of these techniques in determining processing behaviors. The research highlights the superior fidelity of DSC in predicting the relative fraction and type of PE in a PP recyclate. FTIR is also identified as a high‐fidelity approach, albeit requiring application‐specific calibration. TGA, capillary, and oscillatory rheometry are recognized for their ability to distinguish between grades of recycled polyolefins but provide aggregate behaviors rather than detailed constituent information. 3D flow simulation of the cast film extrusion investigated the effect of the viscosity characterization method, non‐isothermal assumption, and process settings but could not fully replicate the observed variations in the cast film processing of two industrial polyolefins with similar melt flow rates and viscosity behaviors. This underscores the practical challenge of predicting processing issues prior to actual processing, necessitating reliance on reliable instrumentation suites and human expertise for diagnosing and remedying variations. HighlightsTwo industrial recycled polypropylene materials having similar melt flow rates exhibit drastically different cast film processing behaviors.DSC and FTIR provide reasonable approaches for identifying constituent materials.Modeling of the melt viscosities characterized by capillary and parallel plate rheology suggests that viscosity variations relative to the power‐law behavior assumed in the coat hanger die design is a predominant driver of cast film instabilities. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Text Encoded Conversion
  • XML
  • Save / Share this Record
  • Send to Email