Tough and fatigue-resistant polymer networks by crack tip softening.

Soft materials fail by crack propagation under external loads. While fracture toughness of a soft material can be enhanced by orders of magnitude, its fatigue threshold remains insusceptible. In this work, we demonstrate a crack tip softening (CTS) concept to simultaneously improve the toughness and threshold of a single polymeric network. Polyacrylamide hydrogels have been selected as a model material. The polymer network is cured by two kinds of crosslinkers: a normal crosslinker and a light-degradable crosslinker. We characterize the pristine sample and light-treated sample by shear modulus, fracture toughness, fatigue threshold, and fractocohesive length. Notably, we apply light at the crack tip of a sample so that the light-sensitive crosslinkers degrade, resulting in a CTS sample with a softer and elastic crack tip. The pristine sample has a fracture toughness of 748.3 ± 15.19 J/m2 and a fatigue threshold of 9.3 J/m2. By comparison, the CTS sample has a fracture toughness of 2,774.6 ± 127.14 J/m2 and a fatigue threshold of 33.8 J/m2. Both fracture toughness and fatigue threshold have been enhanced by about four times. We attribute this simultaneous enhancement to stress de-concentration and elastic shielding at the crack tip. Different from the "fiber/matrix composite" concept and the "crystallization at the crack tip" concept, the CTS concept in the present work provides another option to simultaneously enhance the toughness and threshold, which improves the reliability of soft devices during applications.

Entropymetry for detecting microcracks in high-nickel layered oxide cathodes.

Electric vehicles (EVs) are imposing ever-challenging standards on the lifetime and safety of lithium-ion batteries (LIBs); consequently, real-time nondestructive monitoring of battery cell degradation is highly desired. Unfortunately, high-nickel (Ni) layered oxides, the preferred LIB cathodes for EVs, undergo performance degradation originating from microcrack formation during cycling. Entropymetry is introduced as a real-time analytic tool for monitoring the evolution of microcracks in these cathodes along the state of charge. The entropy change of the layered cathode is associated with the lattice configuration and reflects the structural heterogeneity relevant to the evolution of these microcracks. The structural heterogeneity was correlated with peak broadening in in-situ X-ray diffractometry while varying the experimental conditions that affect crack formation such as the upper cutoff voltage during charging and the Ni-content of the active material. Entropymetry, proposed here as a nondestructive diagnostic tool, can contribute greatly to the safe and reliable operation of LIBs for EVs.

Fracture Resistant CrSi2-Doped Silicon Nanoparticle Anodes for Fast-Charge Lithium-Ion Batteries.

Lithium-ion batteries (LIBs) has been developed over the last three decades. Increased amount of silicon (Si) is added into graphite anode to increase the energy density of LIBs. However, the amount of Si is limited, due to its structural instability and poor electronic conductivity so a novel approach is needed to overcome these issues. In this work, the synthesized chromium silicide (CrSi2) doped Si nanoparticle anode material achieves an initial capacity of 1729.3 mAh g-1 at 0.2C and retains 1085 mAh g-1 after 500 cycles. The new anode also shows fast charge capability due to the enhanced electronic conductivity provided by CrSi2 dopant, delivering a capacity of 815.9 mAh g-1 at 1C after 1000 cycles with a capacity degradation rate of <0.05% per cycle. An in situ transmission electron microscopy is used to study the structural stability of the CrSi2-doped Si, indicating that the high control of CrSi2 dopant prevents the fracture of Si during lithiation and results in long cycle life. Molecular dynamics simulation shows that CrSi2 doping optimizes the crack propagation path and dissipates the fracture energy. In this work a comprehensive information is provided to study the function of metal ion doping in electrode materials.

Oxygen Vacancies Driven by Co in the Deeply Charged State Inducing Intragranular Cracking of Ni-Rich Cathodes.

Intragranular cracking within the material structure of Ni-rich (LiNixCoyMn1 - x - y, x ≥0.9) cathodes greatly threatens cathode integrity and causes capacity degradation, yet its atomic-scale incubation mechanism is not completely elucidated. Notably, the physicochemical properties of component elements fundamentally determine the material structure of cathodes. Herein, a diffusion-controlled incubation mechanism of intragranular cracking is unraveled, and an underlying correlation model with Co element is established. Multi-dimensional analysis reveals that oxygen vacancies appear due to the charge compensation from highly oxidizing Co ions in the deeply charged state, driving the transition metal migration to Li layer and layered to rock-salt phase transition. The local accumulation of two accompanying tensile strains collaborates to promote the nucleation and growth of intragranular cracks along the fragile rock-salt phase domain on (003) plane. This study focuses on the potential risks posed by Co to the architectural and thermal stability of Ni-rich cathodes and is dedicated to the compositional design and performance optimization of Ni-rich cathodes.

Nodulating another way: what can we learn from lateral root base nodulation in legumes?

Certain legumes provide a special pathway for rhizobia to invade the root and develop nitrogen-fixing nodules, a process known as lateral root base (LRB) nodulation. This pathway involves intercellular infection at the junction of the lateral roots with the taproot, leading to nodule formation in the lateral root cortex. Remarkably, this LRB pathway serves as a backbone for various adaptative symbiotic processes. Here, we describe different aspects of LRB nodulation and highlight directions for future research to elucidate the mechanisms of this as yet little known but original pathway that will help in broadening our knowledge on the rhizobium-legume symbiosis.

Impact and torsional behavior of additive layer-manufactured biopolymer: An advancement for orthopedic applications.

Distal ulna locking bone plates (DLBPs) are commonly employed in the treatment of distal ulna fractures. However, commercially available metallic bone plates experience stress shielding and lack corrosion resistance. Poly lactic acid (PLA) is highly favored biopolymer due to its biocompatible and bioabsorbable nature with human tissues. The use of additive layer manufacturing (ALM) is gaining attention for creating customized implants with intricate structures tailored to patient autonomy. ALM-based PLA bone plates must provide high resistance against impact and torsional forces, necessitating the adjustment of printing process parameters. This study focuses on examining the influence of key printing parameters, on the impact strength and torque-withstanding capability of DLBPs. Experimental results, along with microscopic images, reveal that an increase in infill density (IF) and wall thickness imparts strong resistance to layers against crack propagation under impact and torsional loads. On the contrary, an increase in layer height and printing speed leads to delamination and early fracture of layers during impact and torsional testing. IF significantly contributes to improving the impact strength and torque-withstanding capability of DLBPs by 70.53% and 80.65%, respectively. The study highlights the potential of the ALM technique in developing DLBPs with sufficient mechanical strength for biomedical applications.

Microscopic Cracks Modulate Nucleation and Solid-State Crystallization Tendency of Amorphous Celecoxib.

Drugs have been classified as fast, moderate, and poor crystallizers based on their inherent solid-state crystallization tendency. Differential scanning calorimetry-based heat-cool-heat protocol serves as a valuable tool to define the solid-state crystallization tendency. This classification helps in the development of strategies for stabilizing amorphous drugs. However, microscopic characteristics of the samples were generally overlooked during these experiments. In the present study, we evaluated the influence of microscopic cracks on the crystallization tendency of a poorly water-soluble model drug, celecoxib. Cracks developed in the temperature range of 0-10 °C during the cooling cycle triggered the subsequent crystallization of the amorphous phase. Nanoindentation study suggested minimal differences in mechanical properties between samples, although the cracked sample showed relatively inhomogeneous mechanical properties. Nuclei nourishment experiments suggested crack-assisted nucleation, which was supported by Raman data that revealed subtle changes in intermolecular interactions between cracked and uncracked samples. Celecoxib has been generally classified as class II, i.e., a drug with moderate crystallization tendency. Interestingly, classification of amorphous celecoxib may change depending on the presence or absence of cracks in the amorphous sample. Hence, subtle events such as microscopic cracks should be given due consideration while defining the solid-state crystallization tendency of drugs.

External bending of cryodevice during vitrification leads to cryoprotectant cracks and damage to embryo blastomeres.

RESEARCH QUESTION: Embryo blastomeres and the zona pellucida are occasionally damaged during vitrification; is this a result of crack-induced mechanical damage in the glass state, caused by external bending of the device? DESIGN: A stereomicroscope was used to observe external bending-induced cracks in a cryoprotectant. Thereafter, 309 human cleavage-stage embryos derived from abnormally fertilized eggs were used to assess embryo damage under two external bending conditions: forward bending and backward bending, with three bending degrees applied. Three distinct embryo positions were used to examine the correlation between bending and embryo damage. Damage was assessed by looking at blastomere lysis rates, and overall rates of damaged and surviving embryos. RESULTS: A series of parallel cracks were identified in the cryoprotectant used for external bending, which led to damage to the embryo blastomeres. Compared with forward bending and control, the embryos were found to be more easily damaged by backward bending, indicated by significantly higher blastomere lysis and embryo damage rates, and lower embryo survival rate of backward bending than forward bending (P < 0.001). The degree of embryo damage also increased as the degree of external forces increased. Embryo position correlated with degree of embryo damage. CONCLUSIONS: Cryoprotectant crack-induced damage was identified as the cause of embryo damage. Mechanical damage to the glass state occurs because of improper external bending of the cryodevice strip in liquid nitrogen during vitrification. To prevent damage, bending of the strip should be avoided and the embryos should be placed near the tip of the strip.

Investigations on lightweight concrete by in situ compression tests using high-resolution computed tomography (µ-CT).

The fracture behaviour of concrete is studied in various micro- and macro-damage models. This is important for estimating serviceability and stability of concrete structures. However, a detailed understanding of the material behaviour under load is often not available. In order to better interpret the fracture behaviour and pattern, images of lightweight concrete were taken using a high-resolution computed tomography (µ-CT) scanner. The samples were loaded between the taken images and the load was kept constant during the measurement. This study describes the method used and how the data set was analysed to investigate displacements and cracks. It has been shown that displacements and damage to the concrete structure can be detected prior to failure, allowing conclusions to be drawn about the structural behaviour. In principle, the µ-CT measurement can be used to examine different kinds of concrete as well as other systems with inorganic binders and to compare the fracture behaviour of different systems.

Crack cocaine inhalation increases seizure susceptibility by reducing acetylcholinesterase activity.

Crack cocaine is a highly addictive and potent stimulant drug. Animal studies have shown that the cholinergic system plays a role in neurotoxicity induced by cocaine or its active metabolites inhalation. Behavioral alterations associated with crack cocaine use include hyperactivity, depressed mood, and decreased seizure threshold. Here we evaluate the acetylcholinesterase (AChE) and reactive oxygen species (ROS) activity, behavioral profile, and the threshold for epileptic seizures in rats that received intrahippocampal pilocarpine (H-PILO) followed by exposure to crack cocaine (H-PILO + CRACK). Animals exposed to H-PILO + CRACK demonstrated increased severity and frequency of limbic seizures. The AChE activity was reduced in the groups exposed to crack cocaine alone (CRACK) and H-PILO + CRACK, whereas levels of ROS remained unchanged. In addition, crack cocaine exposure increased vertical locomotor activity, without changing water and sucrose intake. Short-term memory consolidation remained unchanged after H-PILO, H-PILO + CRACK, and CRACK administration. Overall, our data suggest that crack cocaine inhalation reduced the threshold for epileptic seizures in rats submitted to low doses of pilocarpine through the inhibition of AChE. Taken together, our findings can be useful in the development of effective strategies for preventing and treating the harmful effects of cocaine and crack cocaine on the central nervous system.

Neurotoxicity of crack cocaine exposure: evidence from a systematic review of in vitro and in vivo studies.

Several studies suggest that crack cocaine users exhibit higher prevalence of both psychiatric and psychosocial problems, with an aggressive pattern of drug use. Nevertheless, few experimental studies attempted to verify the neurotoxicity after crack cocaine exposure, especially when compared with other routes of cocaine administration. This systematic review aimed to verify whether in vitro and/or in vivo crack cocaine exposure is more neurotoxic than cocaine exposure (snorted or injected). A search was performed in the PubMed, EMBASE, Scopus, Web of Science, and LILACS databases for in vitro and in vivo toxicological studies conducted with either rats or mice, with no distinction with regard to sex or age. Other methods including BioRxiv, BDTD, Academic Google, citation searching, and specialist consultation were also adopted. Two independent investigators screened the titles and abstracts of retrieved studies and subsequently performed full-text reading and data extraction. The quality of the included studies was assessed by the Toxicological data Reliability assessment Tool (ToxRTool). The study protocol was registered with the Prospective Registry of Systematic Reviews (PROSPERO; CRD42022332250). Of the twelve studies included, three were in vitro and nine were in vivo studies. According to the ToxRTool, most studies were considered reliable either with or without restrictions, with no one being considered as not reliable. The studies found neuroteratogenic effects, decreased threshold for epileptic seizures, schizophrenic-like symptoms, and cognitive deficits to be associated with crack cocaine exposure. Moreover, both in vitro and in vivo studies reported a worsening in cocaine neurotoxic effect caused by the anhydroecgonine methyl ester (AEME), a cocaine main pyrolysis product, which is in line with the more aggressive pattern of crack cocaine use. This systematic review suggests that crack cocaine exposure is more neurotoxic than other routes of cocaine administration. However, before the scarcity of studies on this topic, further toxicological studies are necessary.

How chain dynamics affects crack initiation in double-network gels.

Double-network gels are a class of tough soft materials comprising two elastic networks with contrasting structures. The formation of a large internal damage zone ahead of the crack tip by the rupturing of the brittle network accounts for the large crack resistance of the materials. Understanding what determines the damage zone is the central question of the fracture mechanics of double-network gels. In this work, we found that at the onset of crack propagation, the size of necking zone, in which the brittle network breaks into fragments and the stretchable network is highly stretched, distinctly decreases with the increase of the solvent viscosity, resulting in a reduction in the fracture toughness of the material. This is in sharp contrast to the tensile behavior of the material that does not change with the solvent viscosity. This result suggests that the dynamics of stretchable network strands, triggered by the rupture of the brittle network, plays a role. To account for this solvent viscosity effect on the crack initiation, a delayed blunting mechanism regarding the polymer dynamics effect is proposed. The discovery on the role of the polymer dynamic adds an important missing piece to the fracture mechanism of this unique material.

Nonsteady fracture of transient networks: The case of vitrimer.

We have discovered a peculiar form of fracture that occurs in polymer network formed by covalent adaptable bonds. Due to the dynamic feature of the bonds, fracture of this network is rate dependent, and the crack propagates in a highly nonsteady manner. These phenomena cannot be explained by the existing fracture theories, most of which are based on steady-state assumption. To explain these peculiar characteristics, we first revisit the fundamental difference between the transient network and the covalent network in which we highlighted the transient feature of the cracks. We extend the current fracture criterion for crack initiation to a time-evolution scheme that allows one to track the nonsteady propagation of a crack. Through a combined experimental modeling effort, we show that fracture in transient networks is governed by two parameters: the Weissenberg number [Formula: see text] that defines the history path of crack-driving force and an extension parameter Z that tells how far a crack can grow. We further use our understanding to explain the peculiar experimental observation. To further leverage on this understanding, we show that one can "program" a specimen's crack extension dynamics by tuning the loading history.

Safe inhalation pipe provision (SIPP): protocol for a mixed-method evaluation of an intervention to improve health outcomes and service engagement among people who use crack cocaine in England.

BACKGROUND: Over 180,000 people use crack cocaine in England, yet provision of smoking equipment to support safer crack use is prohibited under UK law. Pipes used for crack cocaine smoking are often homemade and/or in short supply, leading to pipe sharing and injuries from use of unsafe materials. This increases risk of viral infection and respiratory harm among a marginalised underserved population. International evaluations suggest crack pipe supply leads to sustained reductions in pipe sharing and use of homemade equipment; increased health risk awareness; improved service access; reduction in injecting and crack-related health problems. In this paper, we introduce the protocol for the NIHR-funded SIPP (Safe inhalation pipe provision) project and discuss implications for impact. METHODS: The SIPP study will develop, implement and evaluate a crack smoking equipment and training intervention to be distributed through peer networks and specialist drug services in England. Study components comprise: (1) peer-network capacity building and co-production; (2) a pre- and post-intervention survey at intervention and non-equivalent control sites; (3) a mixed-method process evaluation; and (4) an economic evaluation. Participant eligibility criteria are use of crack within the past 28 days, with a survey sample of ~ 740 for each impact evaluation survey point and ~ 40 for qualitative process evaluation interviews. Our primary outcome measure is pipe sharing within the past 28 days, with secondary outcomes pertaining to use of homemade pipes, service engagement, injecting practice and acute health harms. ANTICIPATED IMPACT: SIPP aims to reduce crack use risk practices and associated health harms; including through increasing crack harm reduction awareness among service providers and peers. Implementation has only been possible with local police approvals. Our goal is to generate an evidence base to inform review of the legislation prohibiting crack pipe supply in the UK. This holds potential to transform harm reduction service provision and engagement nationally. CONCLUSION: People who smoke crack cocaine in England currently have little reason to engage with harm reduction and drug services. Little is known about this growing population. This study will provide insight into population characteristics, unmet need and the case for legislative reform. TRIAL REGISTRATION: ISRCTN12541454  https://doi.org/10.1186/ISRCTN12541454.

Cracks in tensile-contracting and tensile-dilating poroelastic materials.

Fibrous gels such as cartilage, blood clots, and carbon-nanotube-based sponges with absorbed oils suffer a reduction in volume by the expulsion of liquid under uniaxial tension, and this directly affects crack-tip fields and energy release rates. A continuum model is formulated for isotropic fibrous gels that exhibit a range of behaviors from volume increasing to volume decreasing in uniaxial tension by changing the ratio of two material parameters. The motion of liquid in the pores of such gels is modeled using poroelasticity. The direction of liquid fluxes around cracks is shown to depend on whether the gel locally increases or decreases in volume. The energy release rate for cracks is computed using a surface-independent integral and it is shown to have two contributions - one from the stresses in the solid network, and another from the flow of liquid. The contribution to the integral from liquid permeation tends to be negative when the gel exhibits volume decrease, which effectively is a crack shielding mechanism.

Automated Pavement Condition Index Assessment with Deep Learning and Image Analysis: An End-to-End Approach.

The degradation of road pavements due to environmental factors is a pressing issue in infrastructure maintenance, necessitating precise identification of pavement distresses. The pavement condition index (PCI) serves as a critical metric for evaluating pavement conditions, essential for effective budget allocation and performance tracking. Traditional manual PCI assessment methods are limited by labor intensity, subjectivity, and susceptibility to human error. Addressing these challenges, this paper presents a novel, end-to-end automated method for PCI calculation, integrating deep learning and image processing technologies. The first stage employs a deep learning algorithm for accurate detection of pavement cracks, followed by the application of a segmentation-based skeleton algorithm in image processing to estimate crack width precisely. This integrated approach enhances the assessment process, providing a more comprehensive evaluation of pavement integrity. The validation results demonstrate a 95% accuracy in crack detection and 90% accuracy in crack width estimation. Leveraging these results, the automated PCI rating is achieved, aligned with standards, showcasing significant improvements in the efficiency and reliability of PCI evaluations. This method offers advancements in pavement maintenance strategies and potential applications in broader road infrastructure management.

Detection of Road Crack Images Based on Multistage Feature Fusion and a Texture Awareness Method.

Structural health monitoring for roads is an important task that supports inspection of transportation infrastructure. This paper explores deep learning techniques for crack detection in road images and proposes an automatic pixel-level semantic road crack image segmentation method based on a Swin transformer. This method employs Swin-T as the backbone network to extract feature information from crack images at various levels and utilizes the texture unit to extract the texture and edge characteristic information of cracks. The refinement attention module (RAM) and panoramic feature module (PFM) then merge these diverse features, ultimately refining the segmentation results. This method is called FetNet. We collect four public real-world datasets and conduct extensive experiments, comparing FetNet with various deep-learning methods. FetNet achieves the highest precision of 90.4%, a recall of 85.3%, an F1 score of 87.9%, and a mean intersection over union of 78.6% on the Crack500 dataset. The experimental results show that the FetNet approach surpasses other advanced models in terms of crack segmentation accuracy and exhibits excellent generalizability for use in complex scenes.

PCTC-Net: A Crack Segmentation Network with Parallel Dual Encoder Network Fusing Pre-Conv-Based Transformers and Convolutional Neural Networks.

Cracks are common defects that occur on the surfaces of objects and structures. Crack detection is a critical maintenance task that traditionally requires manual labor. Large-scale manual inspections are expensive. Research has been conducted to replace expensive human labor with cheaper computing resources. Recently, crack segmentation based on convolutional neural networks (CNNs) and transformers has been actively investigated for local and global information. However, the transformer is data-intensive owing to its weak inductive bias. Existing labeled datasets for crack segmentation are relatively small. Additionally, a limited amount of fine-grained crack data is available. To address this data-intensive problem, we propose a parallel dual encoder network fusing Pre-Conv-based Transformers and convolutional neural networks (PCTC-Net). The Pre-Conv module automatically optimizes each color channel with a small spatial kernel before the input of the transformer. The proposed model, PCTC-Net, was tested with the DeepCrack, Crack500, and Crackseg9k datasets. The experimental results showed that our model achieved higher generalization performance, stability, and F1 scores than the SOTA model DTrC-Net.

Quantitative Detection of Pipeline Cracks Based on Ultrasonic Guided Waves and Convolutional Neural Network.

In this study, a quantitative detection method of pipeline cracks based on a one-dimensional convolutional neural network (1D-CNN) was developed using the time-domain signal of ultrasonic guided waves and the crack size of the pipeline as the input and output, respectively. Pipeline ultrasonic guided wave detection signals under different crack defect conditions were obtained via numerical simulations and experiments, and these signals were input as features into a multi-layer perceptron and one-dimensional convolutional neural network (1D-CNN) for training. The results revealed that the 1D-CNN performed better in the quantitative analysis of pipeline crack defects, with an error of less than 2% in the simulated and experimental data, and it could effectively evaluate the size of crack defects from the echo signals under different frequency excitations. Thus, by combining the ultrasonic guided wave detection technology and CNN, a quantitative analysis of pipeline crack defects can be effectively realized.

Semantic Segmentation of Surface Cracks in Urban Comprehensive Pipe Galleries Based on Global Attention.

Cracks inside urban underground comprehensive pipe galleries are small and their characteristics are not obvious. Due to low lighting and large shadow areas, the differentiation between the cracks and background in an image is low. Most current semantic segmentation methods focus on overall segmentation and have a large perceptual range. However, for urban underground comprehensive pipe gallery crack segmentation tasks, it is difficult to pay attention to the detailed features of local edges to obtain accurate segmentation results. A Global Attention Segmentation Network (GA-SegNet) is proposed in this paper. The GA-SegNet is designed to perform semantic segmentation by incorporating global attention mechanisms. In order to perform precise pixel classification in the image, a residual separable convolution attention model is employed in an encoder to extract features at multiple scales. A global attention upsample model (GAM) is utilized in a decoder to enhance the connection between shallow-level features and deep abstract features, which could increase the attention of the network towards small cracks. By employing a balanced loss function, the contribution of crack pixels is increased while reducing the focus on background pixels in the overall loss. This approach aims to improve the segmentation accuracy of cracks. The comparative experimental results with other classic models show that the GA SegNet model proposed in this study has better segmentation performance and multiple evaluation indicators, and has advantages in segmentation accuracy and efficiency.