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Development of a Printable Prill Formulation Technique and Demonstration of Monomodal Prill Size on Compaction Density and Compressive Strength
Polymer-bonded explosive molding powder, or “prills,” are relied on for the fabrication of pressed high explosives since the 1950's. The wet granulation technique, also known as “slurry coating,” that is used to formulate prills, is a complex process that results in polydisperse and variable yields. This makes it difficult to study the mesoscale effect that prills have on the microstructure of a pressed article. The following study introduces a novel approach to energetic granulation that leverages techniques used in the additive manufacturing of paste-like energetic materials. This extrusion granulation, or prill printing technique, makes it possible to tailor the sizes and shapes of prills, allowing for their morphological influences to be studied in a controlled manner. The following work details the fabrication and characterization of four monomodal size lots of prills using an inert formulation (95 wt.% melamine, 5 wt.% polymer binder). Prills from each size lot were die-pressed using a fixed recipe to investigate how prill size impacts compaction density and therefore compressive strength. It was found that larger prills influence the pressing density by creating larger defects within the microstructure of a pressed article, resulting in a decrease in compressive strength.
Shear and combustion characterization of printable ammonium perchlorate composite propellant formulations
Seven formulations of ammonium perchlorate composite propellant (APCP) are developed and their properties relevant for successful additive manufacture are characterized. Extrusion in a custom-built 3D printing system and spindle viscometry are used to collect viscosity measurements of curing primary and non-curing secondary versions of the formulations. The formulations that behave similarly to a Bingham plastic, with apparent viscosities between 4 and 8 thousand Pa*s at 30 minutes post-mix, are determined to be most suitable for printing applications. Measurements of one material show a yield stress of 1 kPa. Ambient pressure burn rates of 2.0–2.9 mm/s were measured for the compositions tested. All measured burn rates were comparable to the lower end of typical burn rates for APCP. In conclusion, the results of the characterization demonstrate a propellant suitable for use in a 3D printing system.
Identification and expression of small multidrug resistance transporters in early‐branching anaerobic fungi
Abstract Membrane‐embedded transporters impart essential functions to cells as they mediate sensing and the uptake and extrusion of nutrients, waste products, and effector molecules. Promiscuous multidrug exporters are implicated in resistance to drugs and antibiotics and are highly relevant for microbial engineers who seek to enhance the tolerance of cell factory strains to hydrophobic bioproducts. Here, we report on the identification of small multidrug resistance (SMR) transporters in early‐branching anaerobic fungi (Neocallimastigomycetes). The SMR class of transporters is commonly found in bacteria but has not previously been reported in eukaryotes. In this study, we show that SMR transporters from anaerobic fungi can be produced heterologously in the model yeast Saccharomyces cerevisiae , demonstrating the potential of these proteins as targets for further characterization. The discovery of these novel anaerobic fungal SMR transporters offers a promising path forward to enhance bioproduction from engineered microbial strains.
Magnesium Technology 2020
Magnesium and its alloys are being investigated widely for applications that require extraordinarily high strength-to-weight ratio, vibration damping, electromagnetic shielding, reduction in carbon footprint, sustainability improvements, and low toxicity. In the past decade or so, this drive has led to increased adoption of magnesium and its alloys in everyday products and it is no longer regarded as an esoteric material. The overarching goal of its widespread adoption and replacement of conventional materials such as steel and aluminum alloys has been restricted because of the cost of the material, limited sources of primary material, alloying constraints, high chemical reactivity, and challenges associated with its plasticity. Researchers, scientists, engineers, and economists from industry, government agencies and laboratories, and academic institutions alike are actively developing roadmaps for next-generation products and addressing these challenges as quickly as possible through unique and innovative methods. The TMS Magnesium Committee has been actively involved in providing a platform to these entities for disseminating the latest information, developments, and cutting-edge research and development, and showcasing the latest research and development trends related to magnesium and its alloys through the Magnesium Technology Symposium, which takes place every year at the TMS Annual Meeting. This proceedings volume retains the essence of this longstanding tradition. The twenty-first volume in the series, Magnesium Technology 2020, is the proceedings of the Magnesium Technology Symposium held during the 149th TMS Annual Meeting & Exhibition in San Diego, CA, February 23–27, 2020. The volume captures commentaries and papers from 15 different countries. The papers have been categorized systematically based on topics pertaining to magnesium production, casting and solidification, thermomechanical processing, deformation mechanisms, modeling, corrosion, and applications. The symposium began with keynote sessions that featured several distinguished invited speakers from government organizations and academia, who provided their perspectives on the state of the art, goals, and opportunities in magnesium alloy research and development. Dr. Carlos Tomé from Los Alamos National Laboratory, U.S. Department of Energy, discussed 3D characterization of mechanical twins across grain boundaries. This was followed by a talk on hierarchically structured ultrafine-grained magnesium alloys by Dr. Rajiv Mishra from the University of North Texas, USA, who presented an example of using friction stir additive manufacturing for implementing such microstructures at a component level. Dr. Mark Horstemeyer from Liberty University, USA, presented an overview of fatigue modeling to capture the corrosion-fatigue behavior of magnesium alloys. The final talk in this session was presented by Dr. Bin Jiang from Chongqing University, China, who presented a novel extrusion approach for achieving high-strength magnesium alloy plates.
Differential Property Prediction: A Machine Learning Approach to Experimental Design in Advanced Manufacturing
Advanced manufacturing techniques have enabled the production of materials with state-of-the-art properties. In many cases however, the development of physics-based models of these techniques lags behind their development in the lab. This means that material and process development proceeds largely via trial and error. This is sub-optimal since experiments are cost-, time-, and labor-intensive. In this work we propose a machine learning framework, differential property classification (DPC), which enables an experimenter to leverage machine learning's unparalleled pattern matching capability to pursue data-driven experimental design. DPC takes two possible experiment parameter sets and outputs a prediction of which will produce a material with a more desirable property specified by the operator. We demonstrate the success of DPC on AA7075 tube manufacturing process and mechanical property data using shear assisted processing and extrusion (ShAPE), an emerging solid phase processing technology. We show that by focusing on the experimenter's need to choose between multiple candidate experimental parameters, we can reframe the challenging regression task of predicting material properties from processing parameters, into a classification task on which machine learning models can achieve good performance.
Solutionization via Severe Plastic Deformation: Effect on Natural Aging in an Al-Mg-Si-(Mn) Alloy
Shear Assisted Processing and Extrusion (ShAPE), a severe plastic deformation technique that is fast and scalable, was used to produce thin-wall tubing from alloy 6082 (Al-0.8Mg-0.9Si-0.7Mn) with in-situ solutionization during processing quickly followed by quenching. Quench medium and input material heat treatment were varied and natural aging behavior (T1 heat treatment) was evaluated using tensile testing. As-cast input material was found to have higher strength early in post-ShAPE natural aging and homogenized input material was found to have strengthening during natural aging. Compared to air quenching, water quenching gave greater strength both early in and after natural aging. These observations along with microscopy suggest that: 1. air quenching was too slow; 2. as-cast material was not fully solutionized but plastic deformation broke up the coarse intermetallic particles, which provided strengthening; and 3. homogenized material was solutionized well, which led to good natural aging behavior.
Solid Phase Processing of Mg-Al-Mn-Ca for High Strength and Ductility
While rare-earth Mg alloys have remarkable properties for high strength applications, lower cost alternatives are necessary for the widespread industry use of Mg. Ca added Mg alloys have shown promise as an alternative to rare-earth alloys. Ca-based precipitates can reduce basal texture, reduce casting porosity, and increase mechanical strength. However, the accumulation of Ca-based precipitates along inter-dendritic regions can severely limit ductility. Here, we apply two solid phase processing techniques, friction stir processing and shear assisted processing and extrusion, to produce wrought microstructure sheet and extruded tubes from a cast Mg-Al-Mn-Ca alloy. Ductility of the alloy is enhanced by densification under applied force and elevated temperature, grain refinement, and refinement of (Al,Mg)-Ca based precipitate.
Large-scale reactive thermoset printing: Complex interactions between temperature evolution, viscosity, and cure shrinkage
Thermoset composites are strong candidates for large-scale material extrusion additive manufacturing (AM). However, uncured thermoset composites become unstable as print height increases. Here, chemical initiation of vinyl ester immediately before deposition was used to suppress collapse and enable large-scale thermoset printing. Structural stability was assessed by printing thin walls at various layer times and monitoring thermal gradients with an infrared camera. Stable printing was observed at a layer time of 4.50 min, approximately half the gel time of the material (8 min). Self-weight collapse occurred at short layer time (0.68 min), whereas warpage occurred at long layer time (6.50 min). Here, a new behavior was discovered at intermediate layer time (2.25 min) where the heat generated by the reaction causes new, un-gelled layers to flow. Forced convection eliminates this behavior, stabilizing the 2.25-min layer time print. These findings motivated development of a less exothermic material system, which was used to print a large-scale mold and demonstrate the value of this understanding. By presenting these challenges of large-scale reactive thermoset AM for the first time, this work motivates focused studies of the complex interplay between rheological, thermal, and chemical behaviors to improve the feasibility of large-scale thermoset AM. Tensile properties of the printed material were also measured. Longitudinal and transverse elastic moduli are 3.79 and 2.95 GPa, respectively, and corresponding tensile strengths are 36.11 and 18.83 MPa. The glass transition temperature is 93.13 °C.
Design, fabrication, simulation, and testing of additively manufactured lattice-based copper heat sinks
Here, this study investigates the potential advantages of lattice structure-based bound metal material extrusion (MEX) 3D printing for fabricating high-performance copper heat sinks. Copper powder-filled polymer filaments, with a copper content of > 90 wt.%, were developed specifically for the bound metal MEX 3D printing process. Three types of structures—planar, strut, and surface lattices—were 3D printed to facilitate efficient heat transfer pathways within the heat sinks. Subsequent post-processing steps, including polymer removal and sintering, were performed to achieve dense copper parts. Hot isostatic pressing was further employed to enhance the sintered density from 93 to 98%. Finite element analysis (FEA) simulations were conducted to assess the heat transfer efficiency of the designs, and heat transfer experiments were performed using a custom setup to validate the simulation results. Additionally, this research explores the use of extended hold times during pre-sintering and a reduced atmosphere to enhance the %IACS values (electrical conductivity) and thermal performance of the bound metal MEX 3D printed copper heat sinks. The investigation combines experimental analysis, including simulations and heat transfer experiments, to gain insights into the structure-material property relationships and optimize the thermal performance of the printed heat sinks.
Exploration of fibers produced from petroleum based-mesophase pitch and pet blends for carbon fiber production
Petroleum-derived mesophase pitch and polyethylene terephthalate (PET) were blended and melt-extruded to create precursor fibers. The raw blends, heat treated bulk materials, and fibers were all examined to determine compatibility between petroleum-derived mesophase pitch and PET. Thermal investigation of the raw blends showed the presence of both the pitch and PET in separate phases suggesting no interactions had occurred during mixing. Here, the heat-treated bulk material also showed multiple phases under polarized light while Fourier-transform infrared spectroscopy indicated that the two materials did not fully separate during extrusion. Elemental scans of the precursor fibers showed areas of high oxygen concentrations averaging 11.7% as compared to a 2% oxygen concentration across the majority of the cross-section. Tensile tests of the precursor fibers showed a decrease in average modulus as compared to pure pitch fibers; however, the depressed modulus of the blended fibers was found to be independent of the PET weight percentage. Fibers created from 5 wt.% PET had a strength value within 10% of pure pitch and a 200% increase in modulus and were therefore found to be the most promising for carbon fiber production. Pure pitch and the 5 wt.% PET fibers were stabilized and carbonized to 1000 °C. Both types of fibers were tensile tested to determine their strength and stiffness. Pure pitch carbon fibers maintained a higher strength while the carbon fibers produced from 5 wt.% PET possessed a stiffer modulus which can be attributed to their radial microstructure.
The effect of stretching on polyamide – 6: assessment of crystallinity, mechanical properties, and surface roughness
Polyamide-6 (PA6), or nylon-6, is a widely used low-cost polymer material for various applications. Manufacturing PA6 into fibers involves a spinning process such as melt extrusion, which orients the polymer chains into a semicrystalline structure. When stretching the produced fibers to high strains, the PA6 fibers transition the metastable gamma phase back into the stable gamma phase. The effects of these large stretches on mechanical properties have not been explored after the stretch has been released. In this study, the effects on mechanical properties were studied by stretching the PA6 fibers from 10% to 50% tensile strain and subsequently releasing the fibers. The stretched fibers were characterized by X-ray diffraction and atomic force microscopy to determine the changes to the crystal structure and surface roughness. The stretched fibers were then tensile tested to failure and the tensile properties were examined. The stress-strain curves on the post-stretched PA6 fibers showed clear softening in the fibers with lower initial moduli after 30% stretching. Furthermore, these results may hold a clue to softening of fibers in applications with repeated loading and have implications for mechanical stability and fatigue of this polymeric material.
Enhancement of Nanostructured Ferritic Alloy 14YWT Properties via Heat Treatment for Post-Consolidation Processing
The nanostructured ferritic alloy 14YWT is a promising candidate for in-core use in generation IV nuclear reactors, due to a dense dispersion of insoluble, ultrafine-scale Y-Ti-O nano-oxides, which provide a high degree of irradiation tolerance and thermal stability. This work investigates the effects of heat treatment on the workability of 14YWT, along with the effect of processing history on abnormal grain structures and radial microstructural uniformity. In this study, a 14YWT rod consolidated at 850 °C was heat treated in argon at 1100 °C, 1150 °C, 1200 °C, or 1250 °C for 1 or 8 hours and changes in mechanical properties and microstructure were examined using microhardness and electron backscattered diffraction (EBSD). Two distinct types of large abnormal grains were observed, each with unique processing origins, including one with high and the other with low strain energy. Consolidation via direct extrusion resulted in radial microstructural gradients, where the center of the rod was softer with larger grain sizes and lower strain energies. These gradients persisted and intensified throughout heat treatment. Based upon this work, the recommended heat treatment for increased workability with minimal microstructural change is 1150 °C for 1 hours.
Mechanical Characteristics of Additively Manufactured ODS 316L and 316H Alloys with and Without Post-build Processing
This research aims to explore an accelerated development path for oxide dispersion-strengthened (ODS) alloys by integrating additive manufacturing (AM) technologies with recent advances in ODS materials and traditional manufacturing methods. Novel AM and post-build processing routes have been developed for ODS austenitic alloys, specifically Fe-Cr-Ni alloys like 316L and 316H. Electron microscopy and mechanical characterizations were conducted to evaluate the effects of process variables on microstructure and properties, aiming for an economically feasible route property optimization. Traditionally, ODS alloy production involves multi-day high-energy mechanical milling of alloy powder with yttria (Y 2 O 3 ) followed by powder consolidation via extrusion or other methods and additional thermomechanical processing (TMP) for property control. Here, to address these challenges associated with this complex and costly approach, we propose exploring alternative, cost-effective processing routes focusing on AM and traditional TMP methods. The new ODS alloy processing routes have achieved up to a 400% increase in yield strength and a 60% increase in ultimate tensile strength compared to wrought stainless steels while still maintaining significant ductility and fracture toughness. This paper details the novel and economical AM-based processing routes for ODS austenitic alloys, combined with post-build TMPs, and discusses the mechanical and microstructural characteristics of the developed materials.
Parameters, Properties, and Process: Conditional Neural Generation of Realistic SEM Imagery Toward ML-Assisted Advanced Manufacturing
Abstract The research and development cycle of advanced manufacturing processes traditionally requires a large investment of time and resources. Experiments can be expensive and are hence conducted on relatively small scales. This poses problems for typically data-hungry machine learning tools which could otherwise expedite the development cycle. We build upon prior work by applying conditional generative adversarial networks (GANs) to scanning electron microscope (SEM) imagery from an emerging advanced manufacturing process, shear-assisted processing and extrusion (ShAPE). We generate realistic images conditioned on temper and either experimental parameters or material properties. In doing so, we are able to integrate machine learning into the development cycle, by allowing a user to immediately visualize the microstructure that would arise from particular process parameters or properties. This work forms a technical backbone for a fundamentally new approach for understanding manufacturing processes in the absence of first-principle models. By characterizing microstructure from a topological perspective, we are able to evaluate our models’ ability to capture the breadth and diversity of experimental scanning electron microscope (SEM) samples. Our method is successful in capturing the visual and general microstructural features arising from the considered process, with analysis highlighting directions to further improve the topological realism of our synthetic imagery.
Outcomes and Conclusions from the 2022 AM Bench Measurements, Challenge Problems, Modeling Submissions, and Conference
The Additive Manufacturing Benchmark Test Series (AM Bench) provides rigorous measurement data for validating additive manufacturing (AM) simulations for a broad range of AM technologies and material systems. AM Bench includes extensive in situ and ex situ measurements, simulation challenges for the AM modeling community, and a corresponding conference series. In 2022, the second round of AM Bench measurements, challenge problems, and conference were completed, focusing primarily upon laser powder bed fusion (LPBF) processing of metals, and both material extrusion processing and vat photopolymerization of polymers. In all, more than 100 people from 10 National Institute of Standards and Technology (NIST) divisions and 21 additional organizations were directly involved in the AM Bench 2022 measurements, data management, and conference organization. The international AM community submitted 138 sets of blind modeling simulations for comparison with the in situ and ex situ measurements, up from 46 submissions for the first round of AM Bench in 2018. Analysis of these submissions provides valuable insight into current AM modeling capabilities. The AM Bench data are permanently archived and freely accessible online. The AM Bench conference also hosted an embedded workshop on qualification and certification of AM materials and components.
Design, characterization and shape recovery behavior of 3D/4D printed shape memory polymers (SMPs)
Shape memory polymers (SMPs) represent a paradigm shift in material science, uniquely capable of undergoing reversible shape transformations triggered by external stimuli, positioning them as pivotal in developing next-generation biomedical devices, aerospace components, and adaptive structures. Extensive research has been done on SMPs with a major focus on high-temperature programming methods, which can limit energy efficiency and applicability with temperature-sensitive materials. Additionally, while various SMP blends have demonstrated great potential, limited work has been done on the suitability for 3D printing these materials, particularly under high-strain and ambient temperature programming conditions. In this study, a three-component optimized SMP composition was evaluated by 3D printing via the Material Extrusion (MEX) technique and investigating its ambient temperature-programming behavior at high strains. The SMP formulation studied was a tailored blend of thermoplastic polyurethane (TPU), polycaprolactone (PCL), and an octadecane diol-based copolymer (OBC) that exhibits robust shape memory behavior, high strain tolerance, and efficient force generation. Rigorous thermal, mechanical, and shape recovery analyses, along with optimized printing parameters and consistent shape recovery rates of up to 90%, were achieved under dynamic mechanical analysis (DMA), even under ambient programming conditions. This work demonstrates the SMP composition’s potential for adaptive, self-deployable systems with 4D printing characteristics ideal for bio-inspired structures and artificial muscle fibers.
Thermokinetic mixing compounding for polymer composites – a comprehensive review
High-speed thermokinetic mixers (K-mixers) represent an advanced compounding technology that employs intense shear and friction to convert kinetic energy directly into thermal energy. This mechanism enables rapid mixing cycles, often under one minute, facilitating exceptional filler dispersion while minimizing the material’s thermal history. This is particularly effective for compounding challenging materials, including heat-sensitive biopolymers, wet filler feedstocks, and nanofillers prone to agglomeration. As the first comprehensive review of this technology, this article synthesizes the fundamental principles of thermokinetic mixing (K-mixing) and surveys recent advances in polymer composite fabrication. We contrast the working principles of K-mixers with conventional twin-screw extrusion, highlighting distinct advantages in dispersing nanoscale fillers, exfoliating layered materials, and processing wet cellulosic feedstocks and ultra-high filler loadings (e.g., 85 wt%). Furthermore, strategies to optimize filler–matrix interfacial bonding under rapid-processing constraints, such as the kinetic selection of compatibilizers and fiber surface treatments, are evaluated. Finally, we analyze key structure-processing-property relationships and outline future directions in scaling up, reactive processing, and hybrid material development.