Microstructure Of Materials Research Articles

Probing Particle-Carbon/Binder Degradation Behavior in Fatigued Layered Cathode Materials through Machine Learning Aided Diffraction Tomography.

Understanding how reaction heterogeneity impacts cathode materials during Li-ion battery (LIB) electrochemical cycling is pivotal for unraveling their electrochemical performance. Yet, experimentally verifying these reactions has proven to be a challenge. To address this, we employed scanning μ-XRD computed tomography to scrutinize Ni-rich layered LiNi0.6Co0.2Mn0.2O2 (NCM622) and Li-rich layered Li[Li0.2Ni0.2Mn0.6]O2 (LLNMO). By harnessing machine learning (ML) techniques, we scrutinized an extensive dataset of μ-XRD patterns, about 100,000 patterns per slice, to unveil the spatial distribution of crystalline structure and microstrain. Our experimental findings unequivocally reveal the distinct behavior of these materials. NCM622 exhibits structural degradation and lattice strain intricately linked to the size of secondary particles. Smaller particles and the surface of larger particles in contact with the carbon/binder matrix experience intensified structural fatigue after long-term cycling. Conversely, both the surface and bulk of LLNMO particles endure severe strain-induced structural degradation during high-voltage cycling, resulting in significant voltage decay and capacity fade. This work holds the potential to fine-tune the microstructure of advanced layered materials and manipulate composite electrode construction in order to enhance the performance of LIBs and beyond.

Probing Particle‐Carbon/Binder Degradation Behavior in Fatigued Layered Cathode Materials through Machine Learning Aided Diffraction Tomography

Understanding how reaction heterogeneity impacts cathode materials during Li‐ion battery (LIB) electrochemical cycling is pivotal for unraveling their electrochemical performance. Yet, experimentally verifying these reactions has proven to be a challenge. To address this, we employed scanning μ‐XRD computed tomography to scrutinize Ni‐rich layered LiNi0.6Co0.2Mn0.2O2 (NCM622) and Li‐rich layered Li[Li0.2Ni0.2Mn0.6]O2 (LLNMO). By harnessing machine learning (ML) techniques, we scrutinized an extensive dataset of μ‐XRD patterns, about 100,000 patterns per slice, to unveil the spatial distribution of crystalline structure and microstrain. Our experimental findings unequivocally reveal the distinct behavior of these materials. NCM622 exhibits structural degradation and lattice strain intricately linked to the size of secondary particles. Smaller particles and the surface of larger particles in contact with the carbon/binder matrix experience intensified structural fatigue after long‐term cycling. Conversely, both the surface and bulk of LLNMO particles endure severe strain‐induced structural degradation during high‐voltage cycling, resulting in significant voltage decay and capacity fade. This work holds the potential to fine‐tune the microstructure of advanced layered materials and manipulate composite electrode construction in order to enhance the performance of LIBs and beyond.

The influence of the hydrogenation process on the microstructure and properties of metallic materials

Hydrogen, which belongs to the group of the smallest elements, can freely penetrate the structure of metallic materials and cause enormous damage. This phenomenon may occur due to various conditions and may have different effects on the properties of materials. Understanding these mechanisms is important in the era of changing to alternative energy sources. This situation may occur in combustion engines powered by hydrogen-enriched fuel. The work analyzed the impact of various hydrogenation processes on the properties of aesthetic steel, which is allergic to the formation of carbides at the grain boundaries, such a microstructure is intended to simulate the least favorable working conditions. The work was aimed at evaluating the effects of different hydrogenation methods on changes in the properties of the AISI 310s steel membrane. In the work, electrolytic hydrogenation and heat treatment procedures in a hydrogen atmosphere were used. Investigations of changes in material properties included microhardness and in-situ strength tests in a scanning electron microscope chamber. Research has shown that both processes increase the hardness of materials and change the characteristics of stretching curves.

Lithium Silicate-Based Glass Ceramics in Dentistry: A Narrative Review

Considering the rapid evolution of lithium silicate-based glass ceramics (LSCs) in dentistry, this review paper aims to present an updated overview of the recently introduced commercial novel LSCs. The clinical and in vitro English-language literature relating to the microstructure, manufacturing, strengthening, properties, surface treatments and clinical performance of LSC materials was obtained through an electronic search. Findings from relevant articles were extracted and summarised for this manuscript. There is considerable evidence supporting the mechanical and aesthetic competency of LSC variants, namely zirconia-reinforced lithium silicates and lithium–aluminium disilicates. Nonetheless, the literature assessing the biocompatibility and cytotoxicity of novel LSCs is scarce. An exploration of the chemical, mechanical and chemo-mechanical intaglio surface treatments—alternative to hydrofluoric acid etching—revealed promising adhesion performance for acid neutralisation and plasma treatment. The subtractive manufacturing methods of partially crystallised and fully crystallised LSC blocks and the additive manufacturing modalities pertaining to the fabrication of LSC dental restorations are addressed, wherein that challenges that could be encountered upon implementing novel additive manufacturing approaches using LSC print materials are highlighted. Furthermore, the short-term clinical performance of zirconia-reinforced lithium silicates and lithium–aluminium disilicates is demonstrated to be comparable to that of lithium disilicate ceramics and reveals promising potential for their long-term clinical performance.

Mechanical properties and water resistance study of basic magnesium sulfate cement-emulsified asphalt composite materials

This study introduces a novel semi-flexible composite material (BMSC-EA), formed by merging the favorable properties of emulsified asphalt (EA), known for its high flexibility and crack resistance, with basic magnesium sulfate cement (BMSC), recognized for its high rigidity, early strength, and toughness. The research systematically explores the impact of varying EA dosages on BMSC properties. Furthermore, the study analyzes the phase composition, pore structure, and microstructure of BMSC-EA materials. Results indicate that an increase in EA dosage leads to a corresponding extension in the setting time of BMSC, accompanied by a gradual decrease in compressive and flexural properties. Interestingly, the flexural compression ratio of BMSC increases, suggesting that EA addition significantly enhances BMSC toughness. The principal hydration product of BMSC comprised crystals of 5Mg(OH)2∙MgSO4∙7H2O (5∙1∙7 phase). However, the introduction of EA exerted an inhibitory influence on the generation of Mg(OH)2, leading to a scenario where more MgO remained uninvolved in the hydration reaction. The porosity of the BMSC matrix increases with higher EA content. After subjecting the BMSC-EA material to water immersion treatment, a noteworthy observation emerged: exceptional water resistance was evident when the EA dosage reached 10%. This phenomenon was primarily ascribed to the heightened densification (ultrasonic velocity) observed in the BMSC-EA samples under these conditions. Additionally, the study observes further growth of Mg(OH)2 in BMSC after water immersion treatment, but excessive Mg(OH)2 negatively impacts BMSC-EA. These findings serve as both experimental and theoretical foundations for advancing innovative semi-flexible composite pavement materials.

Physics based models for characterization of machining performance – A critical review

This paper presents a comprehensive review of the concept of machinability by considering the dynamic, tribological, and thermo-mechanical interactions encountered at the tool-chip-machined surface interfaces. The paper provides a demonstration of the capabilities and gaps of the physics-based models for the characterization of the machining performance and the prediction of machinability of difficult-to-cut materials, including additively manufactured (AM) materials, nanocrystalline (NC) materials, fibre reinforced polymers (FRP), metal matrix composites reinforced with ceramic hard particles (MMC), and ceramic matrix composites (CMC). The utilization of efficient computation methods for accurate prediction of force, torque, power consumption, cutting temperature, deflection errors, vibration amplitudes, chatter stability, and thermomechanical interactions in the tool-workpiece system is discussed. The development of thermally-activated dissolution-diffusion wear models to describe the chemical reactions at the tool-chip-workpiece contact interfaces is also presented. These predictions are critical for identifying multi-objectives optimal machining conditions. The integration of predictive machining models within the framework of digital twins in cyber-physical spaces, for in-process monitoring and adaptive control, is demonstrated. Future research for developing new models that can characterize the machinability of AM and NC materials, by considering the effects of varying material microstructure and anisotropy, is presented for conventional and micro-machining operations.

Towards a Digital Twin Framework in Additive Manufacturing: Machine Learning and Bayesian Optimization for Time Series Process Optimization

Laser directed-energy deposition (DED) offers notable advantages in additive manufacturing (AM) for producing intricate geometries and facilitating material functional grading. However, inherent challenges such as material property inconsistencies and part variability persist, predominantly due to its layer-wise fabrication approach. Critical to these challenges is heat accumulation during DED, influencing the resultant material microstructure and properties. Although closed-loop control methods for managing heat accumulation and temperature regulation are prevalent in DED literature, few approaches integrate real-time monitoring, physics-based modeling, and control simultaneously in a cohesive framework. To address this, we present a digital twin (DT) framework for real-time model predictive control of process parameters of the DED for achieving a specific process design objective. To enable its implementation, we detail the development of a surrogate model utilizing Long Short-Term Memory (LSTM)-based machine learning which uses Bayesian Inference to predict temperatures across various spatial locations of the DED-built part. This model offers real-time predictions of future temperature states. In addition, we introduce a Bayesian Optimization (BO) method for Time Series Process Optimization (BOTSPO). Its foundational principles align with traditional BO, and its novelty lies in our unique time series process profile generator with a reduced dimensional representation. BOTSPO is used for dynamic process optimization in which we deploy BOTSPO to determine the optimal laser power profile, aiming to achieve desired mechanical properties in a DED build. The identified profile establishes a process trajectory that online process optimizations aim to match or exceed in performance. This paper elucidates components of the digital twin framework, advocating its prospective consolidation into a comprehensive digital twin system for AM.

The effect of texture on the very high cycle fatigue performance and deformation mechanism of rolled AZ31B magnesium alloys

AbstractRolling can result in anisotropy in the microstructure and mechanical properties of the sheet material. This study focuses on the very high cycle fatigue (VHCF) performance of magnesium alloys in the rolling direction (RD), normal direction (ND), and the bisecting angle between the ND and RD (ND–RD). The findings reveal that RD specimens demonstrate superior fatigue performance, while the ND specimens exhibit the lowest fatigue resistance. During the crack initiation stage, the primary influential factor is the maximum shear stress. Due to c‐axis alignment with ND direction in grains, the deformation mode for ND and RD specimens primarily involves first‐order pyramidal slip, while ND–RD specimens primarily undergo basal slip and prismatic slip. In early stable crack propagation, grain size and texture cause variations in the morphology of the rough area among the three directional specimens. Notably, the RD specimens show faster crack propagation during crack initiation than early stable propagation stage.

A Critical Review on Recent Advancements in Aluminium-Based Metal Matrix Composites

Aluminum matrix composites (AMCs) have garnered significant attention across various industrial sectors owing to their remarkable properties compared to conventional engineering materials. These include low density, high strength-to-weight ratio, excellent corrosion resistance, enhanced wear resistance, and favorable high-temperature properties. These materials find extensive applications in the military, automotive, and aerospace industries. AMCs are manufactured using diverse processing techniques, tailored to their specific classifications. Over three decades of intensive research have yielded numerous scientific revelations regarding the internal and extrinsic influences of ceramic reinforcement on the mechanical, thermomechanical, tribological, and physical characteristics of AMCs. In recent times, AMCs have witnessed a surge in usage across high-tech structural and functional domains, encompassing sports and recreation, automotive, aerospace, defense, and thermal management applications. Notably, studies on particle-reinforced cast AMCs originated in India during the 1970s, attained industrial maturity in developed nations, and are now progressively penetrating the mainstream materials arena. This study provides a comprehensive understanding of AMC material systems, encompassing processing, microstructure, characteristics, and applications, with the latest advancements in the field.

Adaptive residual convolutional neural network for compressive strength prediction of energetic materials using SEM images

The microstructure of materials has a great influence on the macroscopic mechanical properties of materials, and the relationship between them is of great significance to the design of materials. With the development of artificial intelligence and deep learning, many researchers have used convolutional neural networks (CNN) to correlate microscopic images with material properties, and achieved good results. However, for different types of material performance prediction tasks and datasets of different sizes, researchers need to design a special CNN network structure, and the adjustment steps of network structure parameters are cumbersome and time consuming. In this paper, an adaptive residual convolutional neural network with variable depth and width is proposed. We take the prediction error of the test dataset of the specific material performance prediction task as the evaluation index, and adaptively adjusts the network structure based on simulated annealing algorithm to find the best network structure. Finally, it is verified on the dataset composed of scanning electron microscopy (SEM) images and compressive strength of polymer explosive materials. Mean absolute percentage error (MAPE) of our model is 1.3% and the goodness of fit (R2 ) is 0.943. Further, we use Grad-CAM to explore the correlation between material microstructure and material properties.

Impact of Hierarchical Dopant‐Induced Microstructure on Thermoelectric Properties of p‐Type Si‐Ge Alloys Revealed by Comprehensive Multi‐Scale Characterization

AbstractDopant‐induced microstructure in thermoelectric materials significantly affects thermoelectric properties and offers a potential to break the interdependence between electron and phonon transport properties. However, identifying all‐scale dopant‐induced microstructures and correlating them with thermoelectric properties remain a huge challenge owing to a lack of detailed microstructural characterization encompassing all length scales. Here, the hierarchical boron (B)‐induced microstructures in B‐doped Si80Ge20 alloys with different B concentrations are investigated to determine their precise effects on thermoelectric properties. By adopting a multi‐scale characterization approach, including X‐ray diffraction, scanning and transmission electron microscopy, and atom probe tomography, five distinctive B‐induced phases within Si80Ge20 alloys are identified. These phases exhibit different sizes, compositions, and crystal structures. Furthermore, their configuration is comprehensively determined according to B doping concentrations to elucidate their consequential impact on the unusual changes in carrier concentration, density‐of‐states effective mass, and lattice thermal conductivity. The study provides insights into the intricate relationship between hierarchical dopant‐induced microstructures and thermoelectric properties and highlights the importance of investigating all‐scale microstructures in excessively‐doped systems for determining the precise structure‐property relationships.

Experimental study of residual stress distribution in interfacial micro-region of SiCf/Ti17 composites via micro-slotting method

Residual stresses in the interface layer significantly affects the mechanical properties of SiCf/Ti17 composites, which inevitably occurs due to the difference in the thermal expansion coefficient during the fabrication process. Therefore, the micro-residual stress at interface layer of SiCf/Ti17 composites should be quantitatively characterized. In this study, the micro-residual stresses at the interface of the composite are released and mapped via micro-slotting method and subset geometric phase analysis (S-GPA). Based on the material microstructure, a residual stress measurement scheme is designed for the interface layer in the radial and tangential directions. And the deformation field, which is calculated via S-GPA, is released, while the corresponding deformation field is obtained via finite element analysis, so that the residual stress can be fitted by above two deformation fields. The results indicate that, in the cross-setion of the fiber, the residual stresses at carbon interface are tensile, which may be beneficial to improve the mechanical properties of the materials. Meanwhile, tensile residual stresses, instead of compressive stresses in the interface layer, do not inhibit energy dissipation during the fracture of the composite.

Unveiling the role of Atomic-Level “Pump-Driven” effect in MoS2/MnO2 for facilitating directional charge transfer in hybrid capacitive deionization

In addressing the limitations imposed by the inherently low electronic conductivity and substantial ion transfer resistance of transition metal oxides (TMOs) in hybrid capacitive deionization (HCDI) applications, this study delineates a pioneering approach through the fabrication of a MoS2/MnO2 heterostructure, leveraging manganese dioxide (MnO2) as a model system. The investigation underscores the essentiality of constructing high-quality interfaces to act as conduits for directional charge flow, a critical but formidable challenge for enhancing desalination efficacy in electrode materials. By harnessing an atomistic “pump-driven” mechanism, the MoS2/MnO2 heterostructure demonstrably facilitates the promotion of desalination processes, underscored by the establishment of a potent local electric field (IEF) aimed at commanding charge dynamics. Empirical and computational analyses coalesce to unveil the preferential electron transfer from MoS2 to MnO2, a phenomenon precipitated by charge redistribution. This orchestrated charge flow not only augments electronic and ionic transfer efficiencies but also emboldens the MoS2/MnO2 heterostructure with enhanced desalination capabilities. The results show that MoS2/MnO2 demonstrates superior HCDI performance compared to MnO2 in a 500 mg L-1 NaCl solution at 1.2 V, with SRC of 33.21 mg g-1 and SRR of 1.50 mg g-1 min-1. The elucidation of this charge-guided dynamic, achieved through meticulous manipulation of the electronic microstructure and the IEF at the atomic scale, presents a novel paradigm for material science. This research presents an innovative approach for realizing robust charge-guided dynamics through the deliberate manipulation of the electronic microstructure and IEF of materials, employing an atomic-level “pump-driven” effect. This strategy opens new avenues for extending these principles to a broad array of advanced materials.

Synthesis and characterization of coprecipitated layered NCM oxide as cathode for sodium-ion batteries: Kinetics and hydrodynamics studies

Interest in the development of high-performance sodium-ion batteries (SIBs) as a sustainable alternative to lithium-ion batteries (LIBs) for emerging energy storage systems has motivated to delve into a novel approach for the synthesis of layered transition metal oxide (LTMO) type cathode for SIBs batteries. In this study, we introduce novel chemical synthesis method that diverges from traditional methodologies reported till date. Rather than relying on sulfur, nitrate, or acetate metal precursor salts, we employ metal carbonate salt coupled with oxalic acid as a chelating agent, and sodium carbonate as a precipitating agent. This novel chemistry enhances the microstructure of the cathode material inherited from its precursor exhibiting spherical morphology, influence on the electrochemical properties, bestowing the material with high specific capacity, extended cycle life, and an elevated charge–discharge rate. The primary focus of this work centers on a comprehensive investigation of the hydrodynamic and kinetics aspects of the co-precipitation reaction, guided by the principles of chemical engineering. The effects of key parameters such as impeller speed, impeller type, and scale-up effects on the co-precipitation process have been systematically explored. This research introduces insights into optimizing reaction conditions such as pH, reaction temperature, metal precursor salt ratio, precipitating agent, through rigorous experimentation and characterization reports. The notable effect of precipitating agent on morphology has been demonstrated by electron microscopy images. The kinetics study shows the activation energy of 8.9 kJ mol−1 depicts the reaction is controlled by mass transfer resistance and to overcome this effect, impeller type and speed plays significant role and experimentation results shows the axial mixing pattern created by pitched blade impeller is effective to improvise electrochemical properties. The synthesized cathode material exhibits remarkable electrochemical properties, including tap density of approximately 1.3 g cc−1 with reversible capacity of 215 mAh g−1, along with excellent cyclic stability (90 %) over 60 cycles. Furthermore, it shows the high energy density up to 1300 Wh/L and a rapid charge–discharge rate. These findings contribute to the advancement of SIBs technology and offer promising prospects for future researchers to efficient development of high-performance energy storage solutions.

Synthesis of flowerlike vanadium diselenide microspheres for efficient electromagnetic wave absorption.

The revelation of MoS2 as an efficient electromagnetic wave (EMW) absorbing material has ratcheted up people's attention to other transition metal dichalcogenides (TMDs). To date, extensive studies have been conducted on the semiconducting VIB-Group TMDs while research into metallic VB-Group TMDs has been relatively rare. In this work, we successfully fabricated VB-Group VSe2 microspheres through a facile one-step hydrothermal method and used them as EMW absorbers. The flowerlike VSe2 microspheres based on VSe2 nanosheets exhibited a minimum reflection loss of 46.58dB with an effective absorption bandwidth of 4.86GHz. The influence of material morphology, microstructure, and dielectric properties on the EMW absorption performance was systematically investigated. The hierarchically layered structure promoted dielectric loss and EMW absorption by means of multiple reflection, interfacial polarization and related relaxation, and enhanced attenuation ability. This work not only demonstrates that VSe2 is potentially a high-efficiency single component EMW absorber, but also provides fresh insights into exploration on the EMW loss mechanisms of the metallic TMD-based absorbing materials.

Origin of Color and Spectral Characteristics of Nanhong Agate from Northeast Yunnan, China

Nanhong agate has attracted public attention as the most distinctive gemstone in China. Owing to the limited data on Nanhong agates from a new production area in northeastern Yunnan, this paper presents the first data from gemological studies on these agates. Complex investigations using Fourier-transform infrared (FTIR) spectrometry, ultraviolet–visible (UV–VIS) luminescence spectrometry, Raman spectroscopy, polarizing microscopy, scanning electron microscopy (SEM), electron microprobe (EPMA), and laser ablation–inductively coupled plasma mass spectrometry (LA-ICP-MS) analyses were carried out to obtain basic data concerning the gemological properties, microstructure, and spectroscopic and geochemical characteristics of this interesting material. The results illustrate that Nanhong agates from northeastern Yunnan are mainly composed of α-quartz and also contain certain amounts of moganite, illite, goethite, and hematite. The typical red (yellow) and white appearance can be attributed to the microstructure of the agates, the contents of Fe and Al impurities, and trace elements. The Raman spectra, microstructure, and chemical composition of the unique “yellow-skinned” agates from northeastern Yunnan are significantly different from those of other types of Nanhong agate. This work lays a foundation for the future identification and research of this type of Nanhong agate.

Preparation and moisture transport behavior of multilevel branching network nanofiber membrane: Based on the Lattice Boltzmann method and inspired by plant transpiration

Ensuring the efficiency and safety of firefighters relies heavily on optimizing the moisture permeability of their suits. Inspired by the intricate multi-level network structure of plant transpiration, this study utilized electrospinning technology to prepare biomimetic vascular, veined multilevel branched network quick-drying nanofiber membranes. Combining X-ray microtomography (XMT) and the lattice Boltzmann method (LBM), this study conducted a 3D reconstruction of the microstructure of quick-drying nanofiber materials, establishing a characterization method for moisture permeability behavior from a micro to mesoscale perspective and conducted numerical simulations. The results indicate that in the nanofiber membrane, the fiber diameter and pore size between fibers gradually decrease from the inlet to the outlet in the forward flow direction (from PET side to PAN side). At the same displacement pressure difference, the average and maximum flow rates of forward percolation were significantly greater than reverse percolation (from PAN side to PET side); in the initial stage of forward percolation (x < 11), the flow rate first increased and then gradually decreased, with the rate of increase (k = 0.712623) significantly higher than the rate of decrease (k'=0.001102), while in reverse percolation, the flow rate continuously increased throughout the process; These phenomena are primarily due to different startup pressure gradients. Furthermore, the analysis of moisture transport performance indicates that the fiber membrane exhibits highly efficient unidirectional moisture transport capability. This study expands the understanding of the moisture permeability mechanism of nanofibers, which is significant for enhancing the protective performance and comfort of quick-drying firefighter fabrics.

An analytical representation of the 2d generalized balanced power diagram

Tessellations are an important tool to model the microstructure of cellular and polycrystalline materials. Classical tessellation models include the Voronoi diagram and the Laguerre tessellation whose cells are polyhedra. Due to the convexity of their cells, those models may be too restrictive to describe data that includes possibly anisotropic grains with curved boundaries. Several generalizations exist. The cells of the generalized balanced power diagram are induced by elliptic distances leading to more diverse structures. So far, methods for computing the generalized balanced power diagram are restricted to discretized versions in the form of label images. In this work, we derive an analytic representation of the vertices and edges of the generalized balanced power diagram in 2d. Based on that, we propose a novel algorithm to compute the whole diagram.

Mechanical and Corrosion Tests for Magnesium-Zinc/Ti-6Al-4V Composites by Gravity Casting.

A new Mg-4Zn X Ti-6Al-4V (TC4, of 0, 1, and 3 wt.%) alloy was successfully fabricated by a simple and low-cost gravity casting method and heat treatment at 150 °C for 24 h. The composite was examined by XRD, uniaxial tests, FESEM/EDS, potentiostat/EIS, and immersion tests for the material's microstructures, mechanical properties, electrochemical characteristics, and corrosion resistance. Experimental results indicate that heat treatment enables the precipitation of Zn along the Mg grain boundaries and drives the co-precipitation of Al around the TC4 particles and nearby grain boundaries. Uniaxial tensile tests reveal that TC4 reinforces the Mg-Zn matrix material with higher elastic modulus, ultimate tensile stress, and toughness. The heat treatment further enhanced these mechanical properties. Electrochemical tests show that 1 wt.% TC4 composite exhibits the highest open circuit potential among all tested samples, which implies the 1 wt.% TC4-added Mg-Zn is better resistant to the oxidation of the essential metals Mg, Zn, and Al. The immersion tests in the HBSS solution further show that the 1 wt.% TC4 composite has the lowest rise of pH values after 14 days, and EDS for the corroded surface signifies that Mg is the main element vulnerable to oxidation by corrosion.

Acceleration waves in thermoelastic complex media with temperature-dependent phase fields

AbstractWe analyze homothermal acceleration waves in complex materials (those with active microstructure) in the presence of internal constraints that link the temperature to a manifold-valued phase-field describing a generic material microstructure at a certain spatial scale. Such a constraint leads to hyperbolic heat conduction even in the absence of macroscopic strain; we show how it influences the way acceleration waves propagate. The scheme describes a thermoelastic behavior that is compatible with dependence of the free energy on temperature gradient (a dependence otherwise forbidden by the second law of thermodynamics in the traditional non-isothermal description of simple bodies). We eventually provide examples in which the general treatment that we develop applies.