This paper reviews the history of the establishment of dog breeds, summarizes current health and resultant welfare problems and makes some positive suggestions for their resolution. Some breed standards and selection practices run counter to the welfare interests of dogs, to the extent that some breeds are characterized by traits that may be difficult to defend on welfare grounds. Meanwhile, little selection pressure seems to be exerted on some traits that would improve animal welfare and produce dogs better suited to modern society. Unfortunately, the incidence of certain inherited defects in some breeds is unacceptably high, while the number of registered animals of certain breeds within some countries is so low as to make it almost impossible for breeders to avoid mating close relatives. There are several constructive ways to overcome these challenges. Breed associations can ensure that reduction of welfare problems is one of their major aims; they can review breed standards; they can embrace modern technology for animal identification and pedigree checking; they can allow the introduction of ‘new ‘ genetic material into closed stud-books; and they can encourage collaboration with geneticists in identifying and using DNA markers for the control of inherited disorders. There should be a concerted effort to produce and evaluate as companion animals first-cross (F1) hybrids from matings between various pairs of breeds. Finally, geneticists must learn to communicate their science better and in a language that non-geneticists can understand.

Phase-contrast transmission electron microscopy (TEM) is a powerful tool for imaging the local atomic structure of materials. TEM has been used heavily in studies of defect structures of two-dimensional materials such as monolayer graphene due to its high dose efficiency. However, phase-contrast imaging can produce complex nonlinear contrast, even for weakly scattering samples. It is, therefore, difficult to develop fully automated analysis routines for phase-contrast TEM studies using conventional image processing tools. For automated analysis of large sample regions of graphene, one of the key problems is segmentation between the structure of interest and unwanted structures such as surface contaminant layers. In this study, we compare the performance of a conventional Bragg filtering method with a deep learning routine based on the U-Net architecture. We show that the deep learning method is more general, simpler to apply in practice, and produces more accurate and robust results than the conventional algorithm. We provide easily adaptable source code for all results in this paper and discuss potential applications for deep learning in fully automated TEM image analysis.

Honeycomb phononic crystal can obtain wider band gaps in the low frequency based on local resonance theory. Its band structure can be adjustable if we change the height of the cores, which means different kinds of honeycomb phononic crystal can be selected on the basis of different damping demands. Meanwhile, the point defects and line defects affect the localized modes of sound waves and propagation characteristics, the dispersion relations and the displacement fields of the eigenmodes are calculated in the defected systems, as well as the propagation behaviors in the frequency ranges of the band structure, which are also discussed in detail. We constructed the model based on the periodic boundary condition and calculated the band structure according to Bloch theory, and also performed a series of simulation through the COMSOL software, showing that honeycomb has excellent features in reducing noise and vibration, which has a far-reaching influence in designing the new type of acoustic wave devices.

This study investigates the effect of C on the deformation mechanisms in Fe–C alloys by molecular dynamics simulations. In uniaxial tensile simulations, the face-centered-cubic (fcc) structures of Fe–C alloys undergo the following deformation processes: (i) fcc→body-centered-cubic (bcc) martensitic transformation, (ii) deformation of bcc phase, and (iii) bcc→hcp martensitic transformation, which are significantly influenced by the C concentration. For the low C concentrations (0–0.8 wt%) fcc phase, the fcc→bcc phase transformation accords a two-stage shear transformation mechanism based on the Bain model, the deformation mechanism of the bcc phase is the first migration of twinning structures and then elastic deformation, and the bcc→hcp phase transformation follows Burgers relations resulting from the shear of the bcc close-packed layers. However, for the fcc phase with high C concentrations (1.0–2.0 wt%), the fcc→bcc phase transformation follows a localized Bain transformation mechanism impeded by the C atoms, the bcc phase only experiences elastic deformation, and the bcc→hcp phase transformation also conforms to Burgers relations but become localized due to the addition of more C atoms. Because of the different phase transformation mechanisms between the high C and low C supercells, the dislocation generation mechanism is also different.

The remarkable progress in additive manufacturing has promoted the design of architected materials with mechanical properties that go beyond those of conventional solids. Their realization, however, leads to architectures with process-induced defects that can jeopardize mechanical and functional performance. In this work, we investigate experimentally and numerically as-manufactured defects in Ti–6Al–4V octet truss lattice materials fabricated with selective laser melting. Four sets of as-manufactured defects, including surface, microstructural, morphological, and material property imperfections, are characterized experimentally at given locations and orientations. Within the characterized defects, material property and morphological defects are quantified statistically using a combination of atomic force microscopy and micro–computed tomography to generate representative models that incorporate individual defects and their combination. The models are used to assess the sensitivity to as-manufactured defects. Then, the study is expanded by tuning defects amplitude to elucidate the role of the magnitude of as-designed defects on the mechanical properties of the lattice material.

This article presents a brief review of our case studies of data-driven Integrated Computational Materials Engineering (ICME) for intelligently discovering advanced structural metal materials, including light-weight materials (Ti, Mg, and Al alloys), refractory high-entropy alloys, and superalloys. The basic bonding in terms of topology and electronic structures is recommended to be considered as the building blocks/units constructing the microstructures of advanced materials. It is highlighted that the bonding charge density could not only provide an atomic and electronic insight into the physical nature of chemical bond of materials but also reveal the fundamental strengthening/embrittlement mechanisms and the local phase transformations of planar defects, paving a path in accelerating the development of advanced metal materials via interfacial engineering. Perspectives on the knowledge-based modeling/simulations, machine-learning knowledge base, platform, and next-generation workforce for sustainable ecosystem of ICME are highlighted, thus to call for more duty on the developments of advanced structural metal materials and enhancement of research productivity and collaboration.

In this contribution, we use heavy ion irradiation and photoluminescence (PL) spectroscopy to demonstrate that defects can be used to tailor the optical properties of two-dimensional molybdenum disulfide (MoS2). Sonicated MoS2 flakes were deposited onto Si/SiO2 substrate and subjected to 3 MeV Au2+ ion irradiation at room temperature to fluences ranging from 1 × 1012 to 1 × 1016 cm−2. We demonstrate that irradiation-induced defects can control optical excitations in the inner core shell of MoS2 by binding A1s- and B1s-excitons, and correlate the exciton peaks to the specific defects introduced with irradiation. The systematic increase of ion fluence produced different defect densities in MoS2, which were estimated using B/A exciton ratios and progressively increased with ion fluence. We show that up to the fluences of 1 × 1014 cm−2, the MoS2 lattice remains crystalline and defect densities can be controlled, whereas at higher fluences (≥1 × 1015 cm−2), the large number of introduced defects distorts the excitonic structure of the material. In addition to controlling excitons, defects were used to split bound and free trions, and we demonstrate that at higher fluences (1 × 1015 cm−2), both free and bound trions can be observed in the same PL spectrum. Most importantly, the lifetimes of these states exceed trion and exciton lifetimes in pristine MoS2, and PL spectra of irradiated MoS2 remains unchanged weeks after irradiation experiments. Thus, this work demonstrated the feasibility of engineering novel optical behaviors in low-dimensional materials using heavy ion irradiation. The insights gained from this study will aid in understanding the many-body interactions in low-dimensional materials and may ultimately be used to develop novel materials for optoelectronic applications.

The direct laser-deposited Inconel 718 (IN718) specimens were produced using 1073 nm, high power continuous wave (CW), IPG Ytterbium fibre laser and in-situ heat treatment. The laser power and in-situ heat treatment temperature were fixed while varying the laser scanning speed from 0.83 to 2.50 cm/s. The microstructure and micro-hardness of the IN718 specimens were characterized using an optical microscope (OM), scanning electron microscopy (SEM) equipped with an energy-dispersive X-ray spectroscopy (EDS or EDX) and Vickers system. The microstructure of the specimens consists of γ-matrix as the primary phase, Nb-rich particles, constitutional liquation cave, liquation cracking and ductility-dip cracks. It was found that the micro-hardness profile of the IN718 specimens was gradually increased with the increase of the distance from the surface.

Millimetre UO2 single crystals were cut and oriented at JRC Karlsruhe. The orientation of each face of the parallelepiped single crystals was determined with Laue diffraction and the corresponding surface area by geometric measurements. Then, the (111), (100), (110) faces of each single crystal were polished to optical grade and characterized by XRD in order to confirm the surface orientation. The dissolution of the three single crystals was achieved in nitric acid media under dynamic conditions, at room temperature. Two dissolution regimes were observed for all samples. The normalized dissolution rate measured in the first step was not influenced by the crystallographic orientation of the faces. However, during the second step, (110) oriented faces were found to dissolve 4 times faster than the (100) faces. One explanation could involve the atomic composition of each oriented surface in the fluorite-type structure

Concentrated solid-solution alloys (CSAs) demonstrate excellent mechanical properties and promising irradiation resistance depending on their compositions. Existing experimental and simulation results indicate that their heterogeneous structures induced by the random arrangement of different elements are one of the most important reasons responsible for their outstanding properties. Nevertheless, the details of this heterogeneity remain unclear. Specifically, which properties induced by heterogeneity are most relevant to their irradiation response? In this work, we scrutinize the role of heterogeneity in CSAs played in damage evolution in different aspects through atomistic simulations, including lattice misfit, thermodynamic mixing, point defect energetics, point defect diffusion, and dislocation properties. Our results reveal that structural parameters, such as lattice misfit and enthalpy of mixing, are generally not suitable to assess their irradiation response under cascade conditions. Instead, atomic-level defect properties are the keys to understand defect evolution in CSAs. Therefore, tuning chemical disorder to tailor defect properties is a possible way to further improve the irradiation performance of CSAs.

We consider the problem of estimating the rate of defects (mean number of defects per item), given the counts of defects detected by two independent imperfect inspectors on one sample of items. In contrast with the setting for the well-known method of Capture–Recapture, we do not have information regarding the number of defects jointly detected by both inspectors. We solve this problem by constructing two types of estimators—a simple moment-type estimator, and a complicated maximum-likelihood (ML) estimator. The performance of these estimators is studied analytically and by means of simulations. It is shown that the ML estimator is superior to the moment-type estimator. A systematic comparison with the Capture–Recapture method is also made.

With growing demand for better fuel economy for automobiles, multimaterial solutions are increasingly being utilized in the automotive industry for reducing weight in the vehicle body structure. This poses challenges in terms of joining dissimilar metals, especially those with vastly different properties such as aluminum to steel joining. General Motors has developed a new resistance spot-welding technique for dissimilar materials using a multi-ring domed (MRD) electrode and multiple solidification weld schedules to address this challenge. Originally developed for aluminum to aluminum resistance spot welding, this technology is being deployed as the mainstream aluminum joining solution to leverage existing infrastructure and workforce competency in resistance spot welding. With the recent expansion of MRD technology to aluminum to steel resistance spot welding, there is an ever-greater need to experimentally verify the quality of each aluminum to steel resistance spot-weld application with limited time and resources. Nondestructive evaluation (NDE) would enable the transfer of resistance spot-welding technology to dissimilar aluminum to steel joints. This article describes the current state of the art of aluminum to steel resistance spot welding and the challenges in developing a robust NDE process for this technology.

Oxide inclusions such as gray spots are the main defects caused by rail flash butt welding (FBW). An appropriate temperature field and upsetting process are essential for the extrusion of joint impurities. This study constructed a thermomechanical coupling model for the solid-state upsetting process of rail FBW through a combination of finite element simulation and experiment. Subsequently, the effects of different temperature fields and upsetting parameters on the extrusion behavior of impurities were studied. The results show that when the lateral deformation of the joint is not considered, selecting the appropriate upsetting length and increasing the width of the high-temperature plastic zone are beneficial for the extrusion of harmful impurities. Moreover, using variable speed upsetting or increasing the speed of the early upsetting facilitates the extrusion of impurities. However, the impurities in the deeper areas of the rail are difficult to move, and they easily form gray spot defects if the oxide inclusions remain.

Defects in crystalline solids control the properties of engineered and natural materials, and their characterization focuses our strategies to optimize performance. Electron microscopy has served as the backbone of our understanding of defect structure and their interactions, owing to beneficial spatial resolution and contrast mechanisms that enable direct imaging of defects. These defects reside in complex microstructures and chemical environments, demanding a combination of experimental approaches for full defect characterization. In this article, we describe recent progress and trends in methods for examining defects using scanning electron microscopy platforms. Several emerging approaches offer attractive benefits, for instance, in correlative microscopy across length scales and in in situ studies of defect dynamics.

In situ nanomechanical testing in (scanning) transmission electron microscopy provides unique opportunities for studying fundamental deformation processes in materials. New insights have been gained by combining advanced imaging techniques with novel preparation methods and controlled loading scenarios. For instance, by applying in situ high-resolution imaging during tensile deformation of metallic nanostructures, the interplay of dislocation slip and surface diffusion has been identified as the key enabler of superplasticity. Evidence for dislocation pinning by hydrogen defect complexes has been provided by in situ imaging under cyclic pillar compression in a tunable gas environment. And, for the very first time, individual dislocations have been moved around in situ in two-dimensional materials by combining micromanipulation and imaging in a scanning electron microscope.

Raman spectroscopy is a fundamental tool for the characterization of two-dimensional materials. It provides insights into the electronic and vibrational properties of these materials and is particularly rich in features when the incident laser energy approaches the electronic energy transition of the material. Among these features, the double resonance Raman process provides important information on the electron, phonon, and electron–phonon properties. It was on the study of carbon-related materials that the double resonance bands sparkled showing their potential and, since then, have been deeply searched in the study of novel 2D materials. Here, the authors review the double resonance Raman process in 2D materials focusing on graphene and semiconducting MoS2 highlighting the origin of the bands mediated by the two-phonon and phonon–defect processes. The authors discuss the observed properties of the double resonance bands and compare the processes for graphene and MoS2 to find guiding principles for the appearance of double resonance bands. The authors also discuss the new findings of the intervalley scattering process in transition metal dichalcogenides. A brief discussion of the defect-induced bands in both materials is also presented.

Linear elastic moduli of solids with similar chemical compositions usually vary fairly insignificantly. However, for a broad class of apparently similar materials, their higher-order (nonlinear) moduli may differ by many times or even by orders of magnitude. Besides their large magnitude, nonlinear effects often demonstrate qualitative/functional features inconsistent with predictions of the classical theory of nonlinear elasticity based on consideration of weak lattice (atomic) nonlinearity. The latter is mostly applicable to ideal crystals and flawless amorphous solids, whereas the presence of structural heterogeneities can drastically modify the acoustic nonlinearity of materials without appreciable variation in the linear elastic properties. Despite often rather nontrivial/nonstraightforward relationships between microstructural features of the material and the resultant “nonclassical” acoustic nonlinearity, the extremely high structural sensitivity makes utilization of nonlinear acoustic effects attractive for a broad range of diagnostic applications that have been emerging in recent years in various areas—from seismic sounding and nondestructive testing to materials characterization down to the nanoscale.

Thermal conductivity of uranium dioxide (UO2) is an important nuclear fuel performance property. Radiation- and fission-induced defects and microstructures, such as xenon (Xe) gas bubbles, can degrade the thermal conductivity of UO2 significantly. Here, molecular dynamics simulations are conducted to study the effect of Xe bubble size and pressure on the thermal conductivity of UO2. At a given porosity, thermal conductivity increases with Xe cluster size, then reaches a nearly saturated value at a cluster radius of 0.6 nm, demonstrating that dispersed Xe atoms result in a lower thermal conductivity than clustering them into bubbles. In comparison with empty voids of the same size, Xe-filled bubbles lead to a lower thermal conductivity when the number ratio of Xe atoms to uranium vacancies (Xe:VU ratio) in bubbles is high. Detailed atomic-level analysis shows that the pressure-induced distortion of atoms at bubble surface causes additional phonon scattering and thus further reduces the thermal conductivity.

Predicting the structural response of advanced multiphase alloys and understanding the underlying microscopic mechanisms that are responsible for it are two critically important roles that modeling plays in alloy development. The demonstration of superior properties of an alloy, such as high strength, creep resistance, high ductility, and fracture toughness, is not sufficient to secure its use in widespread applications. Still, a good model is needed to take measurable alloy properties, such as microstructure and chemical composition, and forecast how the alloy will perform in specified mechanical deformation conditions, including temperature, time, and rate. Here, we highlight recent achievements using multiscale modeling in elucidating the coupled effects of alloying, microstructure, and mechanism dynamics on the mechanical properties of polycrystalline alloys. Much of the understanding gained by these efforts relies on the integration of computational tools that vary over many length scales and time scales, from first-principles density functional theory, atomistic simulation methods, dislocation and defect theory, micromechanics, phase-field modeling, single crystal plasticity, and polycrystalline plasticity.