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At least 559 records · Page 31

Caloric effects in ferroic materials

The fundamentals and applications of ferroic materials$-$ferromagnetic, ferroelectric, and ferroelastic$-$are common subjects discussed in just about every graduate course related to functional materials. Looking beyond today’s traditional uses, such as in permanent magnets, capacitors, and shape-memory alloys, there are worthwhile and interesting questions common to the caloric properties of these ferroic materials. Can ferroic materials be used in a cooling cycle? Why are these materials susceptible to external fields? Which combination of properties is required to make some of them suitable for efficient cooling and heat pumping? We address these questions in this introduction to ferroic cooling, which comprises magnetocaloric, electrocaloric, elastocaloric and barocaloric approaches and combinations thereof (i.e., multicalorics). These are addressed in greater detail in the articles in this issue.

36 MATERIALS SCIENCE↗

Overcoming fatigue through compression for advanced elastocaloric cooling

Elastocaloric materials exhibit extraordinary cooling potential, but the repetition of cyclic mechanical loadings during long-term operation of cooling systems requires the refrigerant material to have long fatigue life. Here, this paper reviews the fundamental cause of fatigue from aspects of initiation and propagation of fatigue cracks in shape-memory alloys (SMAs) that are used as elastocaloric materials, and highlights recent advances in using compression to overcome fatigue by curtailing the generation of surfaces associated with crack propagation. Compression is identified as a key means to extend fatigue lifetime in engineering design of elastocaloric cooling drive mechanisms. We summarize the state-of-the-art performance of different SMAs as elastocaloric materials and discuss the influence of low cyclic strains and high resistance to transformation. We present integration of compression-based material assemblies into a cooling system prototype and optimization of the system efficiency using work recovery and related measures.

36 MATERIALS SCIENCE↗

A review of materials used in tomographic volumetric additive manufacturing

Abstract Volumetric additive manufacturing is a novel fabrication method allowing rapid, freeform, layer-less 3D printing. Analogous to computer tomography (CT), the method projects dynamic light patterns into a rotating vat of photosensitive resin. These light patterns build up a three-dimensional energy dose within the photosensitive resin, solidifying the volume of the desired object within seconds. Departing from established sequential fabrication methods like stereolithography or digital light printing, volumetric additive manufacturing offers new opportunities for the materials that can be used for printing. These include viscous acrylates and elastomers, epoxies (and orthogonal epoxy-acrylate formulations with spatially controlled stiffness) formulations, tunable stiffness thiol-enes and shape memory foams, polymer derived ceramics, silica-nanocomposite based glass, and gelatin-based hydrogels for cell-laden biofabrication. Here we review these materials, highlight the challenges to adapt them to volumetric additive manufacturing, and discuss the perspectives they present. Graphical abstract

36 MATERIALS SCIENCE↗

Crystallographic variant mapping using precession electron diffraction data

In this work, we developed three methods to map crystallographic variants of samples at the nanoscale by analyzing precession electron diffraction data using a high-temperature shape memory alloy and a VO2 thin film on sapphire as the model systems. The three methods are (I) a user-selecting-reference pattern approach, (II) an algorithm-selecting-reference-pattern approach, and (III) a k-means approach. In the first two approaches, Euclidean distance, Cosine, and Structural Similarity (SSIM) algorithms were assessed for the diffraction pattern similarity quantification. We demonstrated that the Euclidean distance and SSIM methods outperform the Cosine algorithm. We further revealed that the random noise in the diffraction data can dramatically affect similarity quantification. Denoising processes could improve the crystallographic mapping quality. With the three methods mentioned above, we were able to map the crystallographic variants in different materials systems, thus enabling fast variant number quantification and clear variant distribution visualization. The advantages and disadvantages of each approach are also discussed. We expect these methods to benefit researchers who work on martensitic materials, in which the variant information is critical to understand their properties and functionalities.

Crystallographic variant mapping↗

Additive Manufacturing of a y0-Tetragonal Uranium-Niobium Alloy

The ability to process near-net shape structures is of particular interest in applications using rare or expensive materials. Laser powder bed fusion additive manufacturing can meet this challenge, yet also introduces significant processing and materials challenges toward achieving structural integrity. Broadly addressed aspects affecting powder bed fusion structures include surface roughness, residual stresses, and porosity. Here, we focus on materials-specific challenges—namely, the influence of multiple pass reheating during processing and post-processing homogenization on phase transformations and the role of impurities and oxides on grain morphology and mechanical behavior—with a view of adopting laser powder bed fusion processing for the shape memory alloy, uranium-6 wt.% niobium. Our observations to date on the factors influencing material behavior and post-processing requirements and recommendations for process improvement are discussed herein.

36 MATERIALS SCIENCE↗

In Situ High Energy X-ray Diffraction Characterization of Phase Transformations and Mechanical Behaviors in Rapidly Solidified Titanium and Stainless Steel Alloys [Thesis]

Advanced manufacturing techniques like additive manufacturing (AM) have poised themselves to revolutionize metal manufacturing. A wide range of AM techniques are capable of manufacturing metal components with unique, complex geometries and hastening the scientific-engineering-development cycle. Metal AM relies on a layer-by-layer rapid manufacturing process to build components from the substrate up. Rapid solidification is a large departure from traditional metal manufacturing due to its complex physics. Characterization of rapid solidification is difficult, stemming from the small volumes used in AM and the fast dynamics of the process. High energy X-ray diffraction (HEXRD) is a solution to the characterization problems of rapidly solidified alloys and AM. HEXRD can probe small volumes at fast rates and provides a wide range of thermomechanical and kinetic information. This thesis presents the application of HEXRD to rapidly solidified titanium and stainless steel alloys through a series of case studies. In the first two studies, HEXRD is applied to rapidly solidified titanium and stainless steel welds. The materials are characterized for their temperature history, phase changes, kinetics, and microstructural evolution. In the next case study, HEXRD is applied to characterize phase changes in elastocaloric NiTi shape memory alloys (SMAs) under thermomechanical load. HEXRD, in conjunction with other tools, is used to explain the superior performance of the additively manufactured SMAs. In the final two case studies, HEXRD is used to measure the mechanical response of AM parts with complex geometries; namely, the octet truss lattice. Diffraction reveals a wide range of materials information about the AM microstructure including unexpected phases, texture, and mechanical response to loading. The mechanical results from HEXRD and then compared with theoretical predictions about the performance of octet truss lattices. Summarily, HEXRD is a diverse tool that is poised to address the complex characterization problems of many aspects of the additive manufacturing process.

36 MATERIALS SCIENCE↗

Low-Cost Aero Technology Demonstrations

The main focus of this work was to demonstrate the use of polymeric additive manufacturing (AM) to create tooling for both preforming and consolidation. Polymeric tooling was utilized where both modest and higher pressures are used for part consolidation. The key focus for the AM tooling development was for fabrication of complex structures such as ducting, C-channel stiffened skins, and airfoils where conventional male tooling would typically be trapped in the cured part. The AM tooling was evaluated for use as a tool master used to fabricate and re-shape deformable/re-formable mandrels based on SpinTech’s shape memory composite technology known as Smart Tooling. The AM tooling was also evaluated for use as a mold for composite infusion and consolidation. Key performance parameters were tracked for project schedule completion with each step comprising of “art to part” cycle time, cost, and model fidelity for dimensions, performance, and cost. The primary focus of this demonstration was to determine if a 50% cost reduction was achievable, for each AM tooling-set, as compared to conventional processes. UDRI leveraged project partner SpinTech, who manufactures tools and parts in these categories and thus provided a baseline regarding current best practices and provided valuable feedback during the entirety of this demonstration. This demonstration primarily focused on the use of AM tooling for fabrication of three composite component structures which are typically utilized in aircraft and comprise salient geometric features of broad interest. These components are often tooling intensive and have features requiring extraction of male tools which are usually trapped by the geometry. The three structures selected by the team included: 1) A one-piece airfoil shell comprised of compound contours where male tooling would be trapped unless the part were manufactured in two halves as is typically the case. 2) A one-piece duct used for air handling, comprised of compound contours where male tooling would be trapped unless the part were manufactured in two halves, or a washout mandrel were to be used. 3) A co-cured C-channel stiffened skin where typically C-channels would be individually manufactured and then bonded to a cured skin. The demonstration was comprised of three main tasks: • Task 1: AM Tool Feasibility Study – ensure the AM tooling meets the performance requirements as specified by SpinTech to match baseline performance. • Task 2: Complex Tool Demonstration – Fabricate tooling, preforms, and parts representative of an airfoil and duct. • Task 3: Large Aerostructure Fabrication Demonstration – Fabricate tooling, preforms, and part representative of a C-channel stiffened skin. With the conclusion of this project, a decision tree was developed to determine the key considerations necessary to determine if use of AM tooling for the three selected structures was able to attain the same quality as historically achieved on metallic tooling, while providing a significant cost reduction.

36 MATERIALS SCIENCE↗

In-Situ Sensing and Dynamics Predictions for Electrothermally-Actuated Soft Robot Limbs

Untethered soft robots that locomote using electrothermally-responsive materials like shape memory alloy (SMA) face challenging design constraints for sensing actuator states. At the same time, modeling of actuator behaviors faces steep challenges, even with available sensor data, due to complex electrical-thermal-mechanical interactions and hysteresis. This article proposes a framework for in-situ sensing and dynamics modeling of actuator states, particularly temperature of SMA wires, which is used to predict robot motions. A planar soft limb is developed, actuated by a pair of SMA coils, that includes compact and robust sensors for temperature and angular deflection. Data from these sensors are used to train a neural network-based on the long short-term memory (LSTM) architecture to model both unidirectional (single SMA) and bidirectional (both SMAs) motion. Predictions from the model demonstrate that data from the temperature sensor, combined with control inputs, allow for dynamics predictions over extraordinarily long open-loop timescales (10 min) with little drift. Prediction errors are on the order of the soft deflection sensor’s accuracy. This architecture allows for compact designs of electrothermally-actuated soft robots that include sensing sufficient for motion predictions, helping to bring these robots into practical application.

Sabelhaus, Andrew P.↗

Between Harmonic Crystal and Glass: Solids with Dimpled Potential-Energy Surfaces Having Multiple Local Energy Minima

Solids with dimpled potential-energy surfaces are ubiquitous in nature and, typically, exhibit structural (elastic or phonon) instabilities. Dimpled potentials are not harmonic; thus, the conventional quasiharmonic approximation at finite temperatures fails to describe anharmonic vibrations in such solids. At sufficiently high temperatures, their crystal structure is stabilized by entropy; in this phase, a diffraction pattern of a periodic crystal is combined with vibrational properties of a phonon glass. As temperature is lowered, the solid undergoes a symmetry-breaking transition and transforms into a lower-symmetry phase with lower lattice entropy. Here, we identify specific features in the potential-energy surface that lead to such polymorphic behavior; we establish reliable estimates for the relative energies and temperatures associated with the anharmonic vibrations and the solid–solid symmetry-breaking phase transitions. We show that computational phonon methods can be applied to address anharmonic vibrations in a polymorphic solid at fixed temperature. To illustrate the ubiquity of this class of materials, we present a range of examples (elemental metals, a shape-memory alloy, and a layered charge-density-wave system); we show that our theoretical predictions compare well with known experimental data.

36 MATERIALS SCIENCE↗

Recent Trends and Innovation in Additive Manufacturing of Soft Functional Materials

The growing demand for wearable devices, soft robotics, and tissue engineering in recent years has led to an increased effort in the field of soft materials. With the advent of personalized devices, the one-shape-fits-all manufacturing methods may soon no longer be the standard for the rapidly increasing market of soft devices. Recent findings have pushed technology and materials in the area of additive manufacturing (AM) as an alternative fabrication method for soft functional devices, taking geometrical designs and functionality to greater heights. For this reason, this review aims to highlights recent development and advances in AM processable soft materials with self-healing, shape memory, electronic, chromic or any combination of these functional properties. Furthermore, the influence of AM on the mechanical and physical properties on the functionality of these materials is expanded upon. Additionally, advances in soft devices in the fields of soft robotics, biomaterials, sensors, energy harvesters, and optoelectronics are discussed. Lastly, current challenges in AM for soft functional materials and future trends are discussed.

36 MATERIALS SCIENCE↗

Effect of Melt-Spinning Parameters on the Structure and Properties of Ni 55.5 Mn 18.8 Ga 24 Si 1.7 Heusler Alloy Ribbons

Ni–Mn-based Heusler alloys are known to demonstrate magnetic shape memory and giant magnetocaloric effect (MCE). These effects depend on the phases, crystallographic and magnetic phase transitions, and the crystallographic texture characteristics. These structural characteristics, in turn, are a function of the processing parameters. In the current work, Ni 55.5 Mn 18.8 Ga 24 Si 1.7 Heusler alloy was processed by melt-spinning under a helium atmosphere. This process results in a fine microstructure. The ribbon that was produced with a narrower nozzle width, faster wheel speed, and higher cast temperature, indicating a faster cooling rate, had double the magnetic entropy change close to room temperature. However, the other ribbon demonstrated a large entropy change over a broader temperature range, extending its usability. The effect of the melt-spinning process parameters on the developing microstructure, crystallographic structure and texture, transformation temperatures, and the magnetic entropy change were studied to explain the difference in magnetocaloric behavior.

36 MATERIALS SCIENCE↗

Filled Elastomers: Mechanistic and Physics-Driven Modeling and Applications as Smart Materials

Elastomers are made of chain-like molecules to form networks that can sustain large deformation. Rubbers are thermosetting elastomers that are obtained from irreversible curing reactions. Curing reactions create permanent bonds between the molecular chains. On the other hand, thermoplastic elastomers do not need curing reactions. Incorporation of appropriated filler particles, as has been practiced for decades, can significantly enhance mechanical properties of elastomers. However, there are fundamental questions about polymer matrix composites (PMCs) that still elude complete understanding. This is because the macroscopic properties of PMCs depend not only on the overall volume fraction (ϕ) of the filler particles, but also on their spatial distribution (i.e., primary, secondary, and tertiary structure). This work aims at reviewing how the mechanical properties of PMCs are related to the microstructure of filler particles and to the interaction between filler particles and polymer matrices. Overall, soft rubbery matrices dictate the elasticity/hyperelasticity of the PMCs while the reinforcement involves polymer–particle interactions that can significantly influence the mechanical properties of the polymer matrix interface. For ϕ values higher than a threshold, percolation of the filler particles can lead to significant reinforcement. While viscoelastic behavior may be attributed to the soft rubbery component, inelastic behaviors like the Mullins and Payne effects are highly correlated to the microstructures of the polymer matrix and the filler particles, as well as that of the polymer–particle interface. Additionally, the incorporation of specific filler particles within intelligently designed polymer systems has been shown to yield a variety of functional and responsive materials, commonly termed smart materials. We review three types of smart PMCs, i.e., magnetoelastic (M-), shape-memory (SM-), and self-healing (SH-) PMCs, and discuss the constitutive models for these smart materials.

36 MATERIALS SCIENCE↗

Optimizing Magnetic Force Microscopy Resolution and Sensitivity to Visualize Nanoscale Magnetic Domains

Magnetic force microscopy (MFM) enables mapping local magnetic fields across a sample surface with nanoscale resolution. To perform MFM, an atomic force microscopy (AFM) probe whose tip has been magnetized vertically (i.e., perpendicular to the probe cantilever) is oscillated at a fixed height above the sample surface. The resultant shifts in the oscillation phase or frequency, which are proportional to the magnitude and sign of the vertical magnetic force gradient at each pixel location, are then tracked and mapped. Although the spatial resolution and sensitivity of the technique increases with decreasing lift height above the surface, this seemingly straightforward path to improved MFM images is complicated by considerations such as minimizing topographical artifacts due to shorter range van der Waals forces, increasing the oscillation amplitude to further improve sensitivity, and the presence of surface contaminants (in particular water due to humidity under ambient conditions). In addition, due to the orientation of the probe's magnetic dipole moment, MFM is intrinsically more sensitive to samples with an out-of-plane magnetization vector. Here, high-resolution topographical and magnetic phase images of single and bicomponent nanomagnet artificial spin-ice (ASI) arrays obtained in an inert (argon) atmosphere glovebox with <0.1 ppm O 2 and H 2 O are reported. Further, optimization of lift height and drive amplitude for high resolution and sensitivity while simultaneously avoiding the introduction of topographical artifacts is discussed, and detection of the stray magnetic fields emanating from either end of the nanoscale bar magnets (~250 nm long and <100 nm wide) aligned in the plane of the ASI sample surface is shown. Likewise, using the example of a Ni-Mn-Ga magnetic shape memory alloy (MSMA), MFM is demonstrated in an inert atmosphere with magnetic phase sensitivity capable of resolving a series of adjacent magnetic domains each ~200 nm wide.

47 OTHER INSTRUMENTATION↗

Transformation temperatures of martensite in beta phase nickel aluminide

Resistivity and thermal arrest measurements determined that the compositional dependence of Ms (martensite state) temperatures for NiAl martensite was linear between 60 and 69 atomic percent nickel, with Ms = 124 Ni - 7410 K. Resistivity and surface relief experiments indicated the presence of thermoelastic martensite for selected alloys. Some aspects of the transformation were studied by hot stage microscopy and related to the behavior observed for alloys exhibiting the shape-memory effect.

Smialek, J. L.↗

Transformation temperatures of martensite in beta-phase nickel aluminide.

Resistivity and thermal arrest measurements determined that the compositional dependence of M sub s temperatures for NiAl martensite was linear between 60 and 69 at. % Ni, with M sub s = (124 Ni - 7410)K. Resistivity and surface relief experiments for selected alloys indicated the presence of thermoelastic martensite. Some aspects of the transformation were studied by hot-stage microscopy and related to the behavior observed for alloys exhibiting the shape-memory effect.

Smialek, J. L.↗

Passive Sun seeker/tracker and a thermally activated power module

Development and testing of two mechanisms using a shape memory alloy metal (NITINOL) as the power source are described. The two mechanisms developed are a passive Sun Seeker/Tracker and a generic type power module. These mechanisms use NITINOL wire initially strained in pure torsion which provides the greatest mechanical work capacity upon recovery, as compared to other deformation modes (i.e., tension, helical springs, and bending).

Siebert, C. J.↗

Dynamic and structural control utilizing smart materials and structures

An account is given of several novel 'smart material' structural control concepts that are currently under development. The thrust of these investigations is the evolution of intelligent materials and structures superceding the recently defined variable-geometry trusses and shape memory alloy-reinforced composites; the substances envisioned will be able to autonomously evaluate emergent environmental conditions and adapt to them, and even change their operational objectives. While until now the primary objective of the developmental efforts presently discussed has been materials that mimic biological functions, entirely novel concepts may be formulated in due course.

Rogers, C. A.↗