Mechanical property-microstructure relationships of an X70 pipeline steel at elevated temperatures
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Abstract Selective laser sintering (SLS) is an additive manufacturing technology that can provide a novel strategy to manufacture complex polymer‐based composites with tailored properties. In this study, polyamide 12 (PA12) composite powders based on Al 2 O 3 , boron nitride (BN), and carbon nanotubes (CNTs) were prepared via a two‐step mixing approach. Morphology characterization techniques indicated that the fillers were uniformly dispersed in the PA12 matrix as expected. Under the optimum 3D‐printing parameters, the fabrication of SLS parts with high filler loading could be obtained. With 40 wt% Al 2 O 3 , 8 wt% BN, and 2 wt% CNT hybrid fillers, the thermal conductivity of PA12 composites could reach 1.09 W/mK. It could be attributed to the synergistic effect of multi‐dimensional fillers to form dense and continuous thermal conduction paths. The factors influencing the performance of PA12 composites such as melting and crystallization behaviors, dielectric properties, and mechanical properties were also discussed. The results show that these composites have favorable dielectric and mechanical properties. Overall, the PA12 composites fabricated by SLS technology in this study exhibit excellent thermal management ability.
The unproven reliability of perovskite photovoltaics (PVs) is likely to pose an important technical hurdle in the path towards the widespread deployment of the technology. The overall reliability of perovskite PVs is directly afected by the mechanical reliability of the metal halide perovskite material, cells and modules, but this issue has been largely overlooked. Here we stress the importance of addressing the mechanical reliability issue comprehensively. We highlight the important challenges and opportunities, together with best practices, pertaining to the three key interrelated elements that determine the mechanical reliability of perovskite PVs: driving stresses, mechanical properties and mechanical failure. Here, we discuss how to measure the driving stresses and mechanical properties accurately, together with their evolution over time, and the need to understand the relevant failure mechanisms and coupled efects. This efort will inform scientifc approaches to making perovskite PVs more reliable and durable and help them reach their full potential.
Abstract The accumulation of synthetic plastics used in packaging applications in landfills and the environment is a serious problem. This challenge is driving research efforts to develop biodegradable, compostable, or recyclable barrier materials derived from renewable sources. Cellulose, chitin/chitosan, and their combinations are versatile biobased packaging materials because of their diverse biological properties (biocompatibility, biodegradability, antimicrobial properties, antioxidant activity, non-toxicity, and less immunogenic compared to protein), superior physical properties (high surface area, good barrier properties, and mechanical properties), and they can be assembled into different forms and shapes (powders, fibers, films, beads, sponges, gels, and solutions). They can be either assembled into packaging films or used as fillers to improve the properties of other biobased polymers. Methods such as preparation of composites, multilayer coating, and alignment control are used to further improve their barrier, mechanical properties, and ameliorate their moisture sensitivity. With the growing application of cellulose and chitin-based packaging materials, their biodegradability and recyclability are also discussed in this review paper. The future trends of these biobased materials in packaging applications and the possibility of gradually replacing petroleum-based plastics are analyzed in the “Conclusions” section.
Rocks at Earth's surface experience progressive damage due to exposure to environmental conditions. Although environmental damage to rocks is recognized as being time-dependent, our quantitative understanding of its effects on physical and mechanical properties remains limited by field and laboratory studies constrained to short timescales. In this study, we aim to rigorously quantify how these properties evolve under longer natural environmental exposure spanning from the Holocene to the late Pleistocene. We conducted a ‘time series’ analysis of key physical and mechanical rock properties using multiple interior samples from 10 cogenetic granitoid boulders exposed for different amounts of time at two sites in Eastern California, USA. We find that over the late Pleistocene (~30 ka), rocks exhibit porosity increases of 40 ± 4 % and seismic velocity decreases of 7 ± 1 % at both sites. Similarly, over the same time period, rock tensile and compressive strengths declined by an average of 11 ± 4 %, and rock permeability increased on average by 104 ± 50 %. Microscopic analysis of thin sections of the same rocks indicates that microfracture density and intensity also progressively increased over the same timescales. These results suggest that time-dependent fracture propagation due to environmental exposure is likely a central contributor to the observed changes in rock properties. This study provides quantitative documentation that pronounced changes in the physical and mechanical properties of rock progressively occur within thousands of years of exposure.
Here, the effect of testing temperature on mechanical properties and deformation mechanisms was investigated by tensile testing of fine-grained magnesium samples under a range of temperatures (i.e. room temperature 20°C, subfreezing temperatures 0°C, -30°C, and - 60°C) and microstructural observations of both untested and tested samples using electron backscatter diffraction. The results suggest that mechanical properties and deformation mechanisms were significantly affected by lowering testing temperature. Strength increased linearly and ductility decreased linearly with the decrease of testing temperature. Although twinning is generally known to be athermal, this experimental study shows that tensile twinning is the dominating deformation mechanism at room temperature, and that twinning is negligible and dislocation operation is the primary deformation mechanism at 0°C, -30°C, and -60°C
Bamboo fibers (BFs) have high mechanical properties and are candidate reinforcement for epoxy matrix composites. However, to improve performance, good fiber-matrix interaction is required. In this work, unidirectional long BF reinforced epoxy composites at fiber volume content of 22%, 40%, and 50% were made by compression molding. The 40 v% untreated BF reinforced composites exhibited 107% and 439% increase for flexural strength and modulus, respectively, compared to neat epoxy. Sodium hydroxide (NaOH) treatment was used to modify the surface of the BFs, and then the NaOH modified BFs were coated with graphene oxide (GO). The 40 v% NaOH modified BF composites showed an improvement from 259.9 to 327.5 MPa for flexural strength and from 16.7 to 21.5 GPa for flexural modulus, compared to 40 v% untreated BF composites. Slight improvement in properties up to 334.6 MPa for flexural strength and up to 23.8 GPa for flexural modulus was achieved for composites made of 40 v% NaOH/GO modified BF. Surface modification of BF after the NaOH and NaOH/GO treatment was confirmed by X-ray photoelectron spectroscopy and by scanning electron microscopy, which showed differences on the fiber surface morphology and on the composite fracture surface. This BF surface modification approach with GO has potential to impart other properties beyond mechanical to produce multifunctional composite and lead to the use of sustainable plant fibers as alternatives to synthetic fibers.
Metallic glasses are a new class of structural materials which exhibit exciting mechanical properties including high strength and elasticity. In terms of fracture toughness, the material class of metallic glasses spans a wide range; Some metallic glasses are extremely brittle and exhibit near ideal brittle behavior whereas others can be exceptional tough with values comparable to the toughest metals out there. Such large range of observed fracture toughness within the material class of metallic glasses is surprising as they have seemingly a very similar atomic structure. Therefore, we developed “artificial microstructures” which allows to decouple the various contribution of sample geometry, imperfection and structure. Specifically, we decouple variations in the alloys’ chemical composition and the atomic structure and quantified the resulting fracture toughness. Atomic structure of a metallic glass can be modified by the fictive temperature. The fictive temperature of a glass is the temperature at which the liquid metallic glass falls out of equilibrium upon colling and forms a glass. Upon further cooling the structure is maintained only thermal oscillations decrease due to a lower absolute temperature. We found that the effect of fictive temperature (same chemistry, different structural stages of the glass) is comparable to the variations of fracture toughness when the chemistry is varied. Hence, it appears that the subtle differences in the glass structure are responsible for the large range of fracture toughness’s observed. Our results reveal that fracture toughness within the material class of metallic glasses varies significantly and we found some example alloys with exceptional high resistance to fracture and others that are almost ideally brittle. Significant influences on the fracture toughness have the structure of the glass, its chemistry, and some imperfections in the structure.
Abstract Electronic correlations and spin–orbit interactions in plutonium create variations in the bonding behavior of each of its allotropes. In δ -Pu, the 5f electrons lie at the tipping point between itinerant and localized behavior which has made the use of mixed-level models successful in describing its mechanical properties. The mechanism for the emergence of a mixed-level model has not yet been understood. We use a series of density functional theory approximations to understand the interactions that create a mixed-level description of δ -Pu which leads to accurate physical properties. With the intersite interactions present in the hybrid functional, we show that a single 5f electron engages in orbital-selective bonding that can be understood with an Anderson impurity picture. The Anderson model gives us a mechanism to understand how the bonding in δ -Pu evolves as a function of the interactions in the material such that we obtain both the accuracy and physics of the multi-level models from ab initio theory.
The two most common polymorphs in industrial alite, M1 and M3, were characterized at the molecular scale. Different methods were employed and discussed to assess mechanical properties and specific heat of both polymorphs. The calculated homogenized elastic moduli and specific heat were found in good agreement with experimental measurements. A comparative analysis of spacial Youngs modulus reveal isotropic and anisotropic spacial distribution for M{sub 1} and M{sub 3} respectively. A more isotropic compressive strength is also reported for M{sub 1} when compared to M{sub 3} polymorph. Cleavage energies computation allowed to proposed equilibrium shapes for both polymorph, with significant differences. While the lowest cleavage energies were found along (100) and (001) for both polymorphs, the constructed M1 crystal possesses 3 independent facets, against seven for the M3 polymorph.
A stable solid electrolyte interphase (SEI) layer is key to high performing lithium ion batteries for metrics such as calendar and cycle life. The SEI must be mechanically robust to withstand large volumetric changes in anode materials such as lithium and silicon, so understanding the mechanical properties and behavior of the SEI is essential for the rational design of artificial SEI and anode form factors. The mechanical properties and mechanical failure of the SEI are challenging to study, because the SEI is thin at only ~ 10 – 200 nm thick and is air sensitive. Furthermore, the SEI changes as a function of electrode material, electrolyte and additives, temperature, potential, and formation protocols. A variety of in situ and ex situ techniques have been used to study the mechanics of the SEI on a variety of lithium ion battery anode candidates; however, there hasn't been a succinct review of the findings thus far. Because of the difficultly of isolating the true SEI and its mechanical properties, there have been a limited number of studies that can fully de-convolute the SEI from the anode it forms on. A review of past research will be helpful for culminating current knowledge and helping to inspire new innovations to better quantify and understand the mechanical behavior of the SEI. This review will summarize the different experimental and theoretical techniques used to study the mechanics of SEI on common lithium ion battery anodes and their strengths and weaknesses.
Hybrid composites combine two or more different fillers to achieve multifunctional or advanced material properties, such as lightweight and enhanced mechanical properties. The properties of the composites significantly depend on their microstructures, which can be tailored via advanced 3D printing processes. Understanding the process-structure-property relationships is critical to enable the design and engineering of novel hybrid composites for applications in aerospace, automotive, and protective coatings. Here, for this work, we develop 3D printable and lightweight hybrid composites and leverage the conventional design of experiments, a theoretical hybrid model, and an image-driven machine learning (ML) method to investigate their mechanical behaviors. The hybrid composites are formulated with elastomer matrix, microfillers, and thin-shell particles, enabling a significant degree of design freedom of microstructures with densities and mechanical properties varying up to 70% and 91%, respectively. Our statistical analysis indicates that the 3D printing path direction and the microfibers fraction are dominating process parameters with contribution percentages of 45.3% and 57.7% on the specific stiffness and strength, respectively. A hybrid mechanics model is developed based on a simple Weibull distribution function and classical single-filler models to effectively capture the variations in mechanical properties, however, it overestimates the values due to its statistical constraints and idealization of experimental uncertainty. The image-driven ML model leverages the microscale images directly without losing the structural details, shows more accurate predictions with experimental data, and has 48.6% lower root mean square error than the theoretical model.
A large scientific and technological effort is underway to investigate the properties of two‐dimensional (2D) materials to become building blocks in integrated nano‐electronic and photonic circuits, composites, coatings, energy harvesting nano‐ systems, nano‐sensors, and nano‐electro‐mechanical systems (NEMS).While several experiments and calculations have revealed exciting novel phenomena in these nanostructures, many scientific and technological questions remain open. In particular, understanding and controlling the structure and mechanical properties of 2D materials at the interface with a solid surface is of key importance to enable the aforementioned nanotechnologies, as well as to fulfill the potential of strain engineering to tailor their properties. The vision of this DoE research program was to investigate novel mechanical properties and phenomena in 1D and 2D materials with the overarching goal of defining a new basic understanding of mechanical behavior in nano and quantum systems. The group of the PI has developed in the last years several studies on the mechanical properties of Carbon nanotubes and oxide nanobelts, more recently the PI has focused her attention on the properties of two‐dimensional materials, such as graphene and MoS 2 , which are a few‐atomic‐layer thick films and hold a great potential for technological and energy applications. The most studied 2D material is graphene, existing as a single layer of graphite or a few‐layer thick epitaxial graphene film. Graphene possesses a large in‐plane Young’s modulus as well as high intrinsic carrier mobility, and high in‐plane thermal conductivity. Besides graphene, also 2D films of graphene oxide (GO), hexagonal Boron Nitride (h‐BN), and transition metal dichalcogenides such as MoS 2 exhibit unique and excellent properties and hold great promise for nanotechnology applications. This research program was aimed at developing a new basic understanding of the mechanical properties of 1D and 2D materials at the interface with solid substrates, with a focus on the role of defects, materials structure, and substrate interaction. Ultimately, we aimed at developing the basic knowledge and experimental tools for manipulating 1D and 2D materials’ structure, stacking, substrate interaction, defects, and number of layers to realize an entirely new class of ultra‐hard, ultra‐thin, and ultra‐light active materials with ad‐ hoc mechanical properties for a variety of applications.
Advanced experimental and numerical approaches are being developed to capture the localization of plasticity at the nanometer scale as a function of the multiscale and heterogeneous microstructure present in metallic materials. These innovative approaches promise new avenues to understand microstructural effects on mechanical properties, accelerate alloy design, and enable more accurate mechanical property prediction. This article provides an overview of emerging approaches with a focus on the localization of plasticity by crystallographic slip. New insights into the mechanisms and mechanics of strain localization are addressed. The consequences of the localization of plasticity by deformation slip for mechanical properties of metallic materials are also detailed.
Polypropylene (PP) and poly(ethylene terephthalate) (PET) are plastics commonly used for packaging because of their excellent barrier and mechanical properties. The properties of these plastics are often diminished after mechanical recycling, inevitably causing down-cycling. Furthermore, this problem is exacerbated when different kinds of polymers mix. Aramid nanofibers have the potential to improve the mechanical properties of polymers due to their excellent mechanical properties but their poor dispersion in polymers is a challenge. Grafting polymers onto nanofibers can help address this challenge. In this work, different loading levels (1%, 2%, and 5%) of polymer grafted aramid nanofibers (ANFs) are blended with waste PP/PET (90/10), simulating a PP waste stream containing traces of PET contaminants. Scanning electronic microscopy, rheology, and differential scanning calorimetry results show the affinity of PP functionalized aramid nanofibers (PP_ANF) towards the PP matrix. At 1 wt% of the nanofiber, the size of the PET droplets in the PP matrix of the PP_ANF blend range from 0.2 to 2.0 μm while that of unmodified ANF and PET_ANF blends are in the range of 0.1–6.2 and 0.5–7.4 μm, respectively. In summary, polymer grafted ANFs have the tendency of improving properties of its like polymers due to similarity in the grafting polymer and the polymer matrix.
Abstract The reinforcement of mechanically‐weak hydrogels to yield composites with increased stiffness, strength, or toughness is a well‐established approach. In particular, introducing electrospun nanofibers into hydrogels is a common strategy for biomedical applications, as the resulting hierarchical structure mimics biology and allows for control over fiber diameter and alignment and tuning of mechanical properties. However, further study of the link between the constituent materials and the mechanical properties of the composite is uncommon. One potential model to understand the mechanical properties of fiber‐reinforced hydrogels involves the Halpin–Tsai equations, which relate the modulus values of the fibers and hydrogel matrix and the fiber volume fraction, to the modulus of the composite. To assess the application of this model to fiber‐reinforced hydrogels, predicted values were compared with experimental values from mechanical testing of a poly(ethylene glycol) (PEG) matrix reinforced with an electrospun polycaprolactone (PCL) fiber mat. Although the equations described these systems well in tension, providing a facile approach to identify a fiber volume fraction that will achieve a desired modulus, the Halpin–Tsai approach was less successful under compression. This study motivates additional investigation of the role of structural features of hydrogel composites in determining mechanical properties to enable design of materials for specific applications.
Quality control of Laser Powder Bed Fusion (PBF-LB) additively manufactured parts is an important hurdle inhibiting the technology’s use structural applications. Acoustic monitoring of the laser powder bed fusion process can detect defects in-situ that are known to degrade mechanical properties. However, processing-structure-property (PSP) relationships are required to extrapolate from detected defects to part performance. Here, this study explores how acoustics may be a suitable signature linking processing conditions to properties, thus effectively substituting for structure in the PSP relationship. Establishing such a relationship would enable a part’s mechanical performance to be directly predicted from its acoustic signature, reducing the need for destructive testing or microstructural analysis to ensure a part will meet performance requirements. One hundred CoCrFeMnNi high entropy alloy tensile bars were printed across 13 process conditions in a series of 6 prints. The acoustic signatures of these tensile bars were used to train machine learning models to predict each part’s mechanical properties. By using both process information and acoustic information to predict mechanical properties, yield strength was predicted 18% more accurately and ductility to failure was predicted 10% more accurately than is achieved when using duplicate parts to predict part performance. Finally, individual acoustic frequencies were investigated to determine why acoustic signatures improve mechanical property predictions and the potential physical origins of these signatures. This work demonstrates how blending acoustics, process information, and machine learning can provide in-situ diagnostics of mechanical properties and improve the reliability of the PBF-LB process.
Alkali-silica reaction (ASR) is a major deterioration mechanism that affects the durability of concrete structures. As the slow rate of ASR development and the restrained expansion in field concrete might affect the development of ASR damage, an experimental program was performed to investigate the effects of the rate of ASR expansion and confinement on the degradation of mechanical properties of concretes. Literature data on the degradation of mechanical properties of concretes with ASR expansion were collected and analyzed to investigate the influence of the rate of ASR expansion and confinement on the degradation trends. Degradation of mechanical properties was found to be significantly influenced by the rate of ASR expansion and slightly affected by confinements. The slow rate of ASR expansion seems to be beneficial in limiting concrete degradation. The effects of confinement seem to be related to the direction of restraint and crack orientations.