Surface Strain Research Articles

A Novel Axial Load Inversion Method for Rock Bolts Based on the Surface Strain of a Bearing Plate

Anchor rock bolts are among the essential support components employed in coal mine support engineering. Measuring the axial load of the supporting anchor bolts constitutes an important foundation for evaluating the support effect and the mechanical state of the surrounding rock. The existing methods for measuring the axial load of rock bolts have difficulty meeting the actual demands in terms of accuracy and means. Therefore, we propose a novel inverse method for determining the axial load of rock bolts. On the basis of the dynamic relationship between the axial load of the anchor bolt and the strain of the plate, a calculation model for the inverse analysis of the axial load from the plate strain is presented, and it is verified and corrected through finite element analysis and indoor physical experiments. By combining the calculation model with the digital image correlation method, a low costinversion of the axial load of the anchor bolt in actual support engineering is achieved. The experimental results demonstrate that the average errors of the load inversion of anchor bolts in three different states via the theory and method proposed in this paper are less than 8.8% (4 kN), 3.6% (3.2 kN), and 14.7% (5.5 kN), respectively, and the average error of the axial load of the rock bolts in the proposed method is only 4.23 kN. It possesses relatively high accuracy and can be effectively applied in the actual production processes of mines.

Improving the crystallinity of quaternary sputtered CIGS absorber layer properties via optimized deposition and annealing temperature

This study presents a method to improve Cu(In1−xGax)Se2 (CIGS) absorber layer performance through an annealing technique that enhances the quality of as-deposited CIGS films. CIGS films were deposited on soda-lime glass substrates using RF magnetron sputtering at 300 °C, 400 °C, and 500 °C, followed by annealing at 500 °C for 30 min. By annealing, the crystal structure of the CIGS films is aligned, and surface strain is minimized. It can significantly boost the films’ crystallinity, crystallite sizes, carrier concentration, mobility, and energy gap. The highest temperatures enhanced crystallinity due to larger crystallite size, resulting in lower resistivity. The properties improvements are crucial for optimizing CIGS absorber layer performance. Complete CIGS solar cell at 300 °C yield Voc = 253 mV, Jsc = 1.78 mA/cm2, and efficiency = 0.15 %.

Comprehensive theoretical study of the effects of facet, oxygen vacancies, and surface strain on iron and cobalt impurities in different surfaces of anatase TiO2.

We report the results of systematic ab initio modelling of various configurations of iron and cobalt impurities embedded in the (110), (101), and (100) surfaces of anatase TiO2, with and without oxygen vacancies. The simulation results demonstrate that incorporation into interstitial voids at the surface level is significantly more favourable than other configurations for both iron and cobalt. The calculations also demonstrate the crucial effect of the facet as well as the lesser effects of other factors, such as vacancies and strain on the energetics of defect incorporation, magnetic moment, bandgap, and catalytic performance. It is further shown that there is no tendency towards the segregation or clustering of impurities on the surface. The calculated free energies of the hydrogen evolution reaction in acidic media predict that iron impurities embedded in the (101) surface of anatase TiO2 can be a competitive catalyst for this reaction.

Analytic modeling and validation of strain in textile-based OLEDs for advanced textile display technologies

In the IoT era, the demand for wearable displays is rapidly growing, catalyzing the advancement of research into textile-based organic light-emitting diodes (OLEDs). This growing interest stems particularly from the inherent flexibility of textile-based OLEDs1,2, allowing for seamless integration into the dynamic and interactive functionalities of cutting-edge wearable technology, alongside their superior electrical performance. The durability and mechanical robustness of these displays, especially under physical stress and deformation, are critical to their practical application and longevity. Thus, understanding and enhancing the mechanical properties of textile-based OLEDs is paramount for their successful integration into wearable technologies. However, many studies assessing the mechanical properties of OLEDs have predominantly relied on simplistic bending test outcomes determined by the radius, often neglecting or insufficiently analyzing the strain exerted on the OLEDs atop textile substrates in relation to curvature of these devices. Existing analyses typically presume pure bending, though such an assumption leads to considerable errors in strain estimations, making such approaches problematic if the goal is practical application in actual wearable display products. To address these limitations, an analytic model that includes a comprehensive energy equation is introduced, considering the stretching energy, bending energy, and shear energy of each layer composing the textile substrate. This holistic approach provides a novel formula specifically designed to calculate the top surface strain of textile substrates. Robust validation of this formula is conducted by comparing its results with strain measurements obtained from digital image correlation (DIC) and finite element analysis (FEA) outcomes from ANSYS across various bending radii (or equivalently, curvatures). The close alignment of the calculated strain values with those derived from DIC and FEA not only underscores the precision of this formula but also highlights its significant potential for enhancing the designs and functionalities of future wearable display technologies under real-world conditions.

Formulation and evaluation of herbal shampoo

The main objective of these study is to evaluate and formulate herbal shampoo. Shampoo are one of the cosmetic products used in daily life. Synthetic preservatives and detergents have sometimes been the cause of adverse effects among consumers. A more radical approach in reducing the synthetic ingredients is by incorporating natural ingredients whose functionality is comparable with their synthetic ingredients. The ingredients used in formulation of Herbal Shampoo are Ficus Religiosa leaves (Powder), Hibiscus Leaves (Powder), Reetha (Powder), Shikakai (Powder), Aloevera, then prepared by mixing with each other and evaluated for its organoleptic and physio-chemical characteristics and performance tests in terms of wetting time test, pH, solid contents, surface tension, dirt dispersion, foam Stability, and Viscosity was performed. The combination of several such ingredient of herbal origin has made it possible to secure highly effective dry powder shampoo. The formulation at laboratory scale was done and evaluated for number of parameters to ensure its safety and efficacy The Formulated Herbal Shampoo was clear and good appealing. It demonstrated good froth stability, detergency, good cleansing, small bubble size, low surface strain, and execution of good conditioning property. The physicochemical evaluation of the formulated shampoo showed ideal results. However, to improve its quality, product performance, and safety, further development was required.

Surface Strain Measurement for Non-Intrusive Internal Pressure Evaluation of a Cannon

Abstract Recent cutting-edge designs for gun barrels, projectiles, and propellants require testing, such as measuring the internal pressure during firing. However, there are concerns with the current drilling method to mount pressure transducers near the breech and chamber of the gun barrel where pressure is highest. To address this challenge, the team hereby presents an alternative, nonintrusive strain measurement method. This method focuses on determining the feasibility and accuracy of relating tangential strain along the sidewall of a gun barrel to the drastic internal pressure rise created during combustion. A transient structural, numerical model of a 155 mm gun barrel was created using ansys. The pressure was derived using the outline in Interior Ballistics of High Velocity Guns, version 2, and the model was validated using published experimental tangential strain testing data from a gun of the same caliber. The model was then used to demonstrate the ideal location for strain measurement along the sidewall of the chamber. Furthermore, three different pressure ranges were simulated in the model. The behavior of the tangential strain in each case indicates a similar trend to the internal pressure rise and oscillation due to a dominant frequency of the barrel. A method to predict internal pressure from external tangential strain was developed. The internal pressure predicted is within 4% of the pressure applied in the model. In the sensitivity study, the thickness and elastic modulus of the gun barrel were found to be the primary factors affecting tangential strain. Overall, this work helps to understand tangential strain behavior on the sidewall of a large-caliber gun barrel and lays the ground for an accurate prediction of internal pressure from external tangential strain.

Optimizing the ORR performance of PtMnM ternary intermetallics by tuning the surface strain

Optimizing the ORR performance of PtMnM ternary intermetallics by tuning the surface strain

Enhanced Regulation of Selectivity by the Coupling Effects of Surface Acidity and Strain Effects via Precisely Controlling the Location of Pt.

Loading a sensitizer and constructing a rational nanostructure have been reported to be effective approaches for enhancing the catalytic/sensing performance. However, the impact of the precise loading position on the catalytic/sensing performance is always overlooked. Here, we discovered that precisely changing the location of Pt clusters from the outside of Al2O3-ZnO nanocoils (O-PtAlZnNCs) to the inner side of the nanocoils (I-PtAlZnNCs) could change the sensing performance of the sensor from H2S to acetone. Furthermore, precisely loading Pt inside of the confined space led to a high sensing performance and reduced the limit of detection (LOD) of acetone by a factor of 50 times (from 100 to 2 ppb). Combining X-ray photoelectron spectroscopy (XPS), NH3-diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), in situ X-ray absorption spectroscopy (XAS), and density functional theory (DFT) simulations, the enhancement of sensitivity and regulation of sensing selectivity are attributed to the coupling effects from enrichment of confined space and Al2O3 acid-base active sites as well as the regulation of electronic structure by location-dominated strain effects. This work not only provides a novel sight to precisely regulate the selectivity and obtain ultrasensitive materials but also serves as a useful instruction for further understanding and precisely designing specific sensors and catalysts with high performance.

Advanced monitoring of damage behavior and 3D visualization of fiber distribution in assessing crack resistance mechanisms in steel fiber-reinforced concrete

This study presents a novel approach to understanding the reinforcing mechanisms of steel fiber-reinforced concrete, particularly its crack resistance and toughening effects. By integrating dynamic surface strain monitoring with advanced three-dimensional visualization techniques, new insights are provided into how steel fibers enhance concrete's structural performance. X-ray computed tomography (CT) technology enabled detailed 3D visualization and analysis of steel fibers embedded within the concrete matrix, facilitating an in-depth examination of their distribution patterns, orientation, and positioning. Additionally, the Digital Image Correlation (DIC) three-dimensional full-field strain measurement system was utilized to dynamically monitor the loading process during three-point bending tests on semicircular concrete specimens. The findings indicate that the uniform distribution of steel fibers significantly reduces stress concentration and effectively delays crack initiation and propagation. Steel fibers bridge cracks, mitigate local stress concentrations, and substitute for the tensile components of concrete after macro-crack formation, thereby inhibiting further crack propagation. Quantitative analysis of fiber distribution through 3D image reconstruction and coordinate extraction confirmed a strong correlation between fiber orientation and crack resistance. This study contributes to the field by offering a comprehensive analysis of key parameters such as fracture process strain monitoring, 3D visualization, and quantification of fiber distribution, advancing the understanding of crack propagation mechanisms and failure processes in fiber-reinforced concrete.

Machine Learning‐Aided Discovery of Low‐Pt High Entropy Intermetallic Compounds for Electrochemical Oxygen Reduction Reaction

Advancing the design of cathode catalysts to significantly maximize platinum utilization and augment the longevity has emerged as a formidable challenge in the field of fuel cells. Herein, we rationally design a high entropy intermetallic compound (HEIC, Pt(FeCoNiCu)3) for catalyzing oxygen reduction reaction (ORR) by an efficient machine learning stategy, where crystal graph convolutional neural networks are employed to expedite the multicomponent design. Based on a dataset generated from first‐principles calculations, the model can achieve a high prediction accuracy with mean absolute errors of 0.003 for surface strain and 0.011 eV atom‐1 for formation energy. In addition, we identify two chemical features (atomic size difference and mixing enthalpy) as new descriptors to explore advanced ORR catalysts. The carbon supported Pt(FeCoNiCu)3 catalyst with small particle size is successfully synthesized by a freeze‐drying‐annealing technology, and exhibits ultrahigh mass activity (4.09 A mgPt‐1) and specific activity (7.92 mA cm‐2). Meanwhile, The catalyst also shows significantly enhanced electrochemical stability which can be ascribed to the sluggish difussion effect in the HEIC structure. Beyond offering a promising low‐Pt electrocatalysts for fuel cell cathode, this work offers a new paradigm to rationally design advanced catalysts for energy storage and conversion devices.

Machine Learning-Aided Discovery of Low-Pt High Entropy Intermetallic Compounds for Electrochemical Oxygen Reduction Reaction.

Advancing the design of cathode catalysts to significantly maximize platinum utilization and augment the longevity has emerged as a formidable challenge in the field of fuel cells. Herein, we rationally design a high entropy intermetallic compound (HEIC, Pt(FeCoNiCu)3) for catalyzing oxygen reduction reaction (ORR) by an efficient machine learning stategy, where crystal graph convolutional neural networks are employed to expedite the multicomponent design. Based on a dataset generated from first-principles calculations, the model can achieve a high prediction accuracy with mean absolute errors of 0.003 for surface strain and 0.011 eV atom-1 for formation energy. In addition, we identify two chemical features (atomic size difference and mixing enthalpy) as new descriptors to explore advanced ORR catalysts. The carbon supported Pt(FeCoNiCu)3 catalyst with small particle size is successfully synthesized by a freeze-drying-annealing technology, and exhibits ultrahigh mass activity (4.09 A mgPt-1) and specific activity (7.92 mA cm-2). Meanwhile, The catalyst also shows significantly enhanced electrochemical stability which can be ascribed to the sluggish difussion effect in the HEIC structure. Beyond offering a promising low-Pt electrocatalysts for fuel cell cathode, this work offers a new paradigm to rationally design advanced catalysts for energy storage and conversion devices.

In-vivo left atrial surface motion and strain measurement using novel mesh regularized image block matching method with 4D-CTA

Atrial strain and motion play important roles in evaluation of stroke risks for patients with atrial fibrillation. While cardiac computed tomographic angiography (CTA) provides detailed left atrial morphology with unparallel image resolution, finding a suitable strain measurement method for CTA remains a considerable challenge. In this paper, for the first time, we introduced a mesh regularized image block matching method to estimate 3D left atrial (LA) surface strain with 4D CTA. A series of performance tests with ex-vivo phantom and in-vivo 4D-CTA data were deployed. In conclusion, our proposed method could provide reliable LA motion and strain data within limited time.

Two-dimensional thermal and dynamical strain in landfast sea ice from InSAR: results from a new analytical inverse method and field observations

Abstract Observing continuous strain in sea ice at geophysical scales of tens of meters to kilometers requires displacement measurements made with millimeter-scale precision. Satellite-based interferometric synthetic aperture radar (InSAR) provides such precise measurements of relative surface displacement over broad spatial areas at regular intervals and, unlike point displacement measurements, it allows confident delineation of continuously deforming regions. However, InSAR only captures the 1-D component of surface displacement parallel to a radar's lines-of-sight. Additional analysis is required to translate between these 1-D observations and the horizontal or vertical displacements they arose from. Previous studies utilize an iterative inverse model to constrain estimates of horizontal surface displacement from InSAR. Here we build upon that work outlining a new analytical inverse modeling method for quantifying displacement and strain over continuous regions of sea ice and provide comparison between model results and independent displacement observations. We demonstrate the inverse method over both landfast and drifting ice along the Alaskan coastline. These intercomparisons highlight environments in which displacements inverted from interferograms may be used as an independent estimator of surface strain, as well as the potential for the outlined inverse methods to be used in conjunction with other observing methods.

Enhancing charge-emitting shallow traps in metal halide perovskites by >100 times by surface strain

Enhancing charge-emitting shallow traps in metal halide perovskites by >100 times by surface strain

Bond-slip behavior of Aluminum Alloy (AA) bars for near-surface mounted (NSM) technique

An experimental study consisting of 22 pull-out tests was carried out to investigate the bond-slip performance and load transfer mechanism between near-surface mounted (NSM) Aluminum Alloy (AA) bars and concrete when the AA bars are inserted into pre-cut grooves on the surface of the host structure and bonded with an appropriate bonding agent. The effects of several design parameters were evaluated including bond length, diameter of AA bars, bar surface treatment, and adhesive type. A digital image correlation (DIC) system was used to measure the slips and surface strain and four failure modes were observed in the tests, being concrete splitting failure, epoxy splitting, debonding at the bar-epoxy interface, and AA bar rupture. Results showed that an increase in bond length could make the failure mode more ductile, while AA bars with rough surfaces exhibited a relatively satisfactory bond-slip behavior when a suitable epoxy was used. Finally, the test data from this study were used to examine three bond-slip models based on fiber reinforced polymers (FRP) for the NSM technique. A new bond-slip model considering the influence of the bar external surface was proposed and validated by the test results from both this study and literature.

Morphological and Structural Characterization of Shortening Landforms on Mars

AbstractThe lithosphere of Mars accommodates horizontal shortening through folding and faulting, producing landforms described as wrinkle ridges or lobate scarps. Despite this nomenclature, we lack a deep understanding of the drivers of morphological differences observed between landform types. This study aims to develop a quantitative model for shortening landform classification based on surface morphology, subsurface architecture, and strain accommodation, facilitating interpretations of where and how lithospheric stresses are recorded. We developed this model by mapping 100 shortening landforms in a Geographic Information System, recording 12 unique geomorphic parameters such as length and asymmetry, and estimating the strain of each landform. We conducted a Discriminant Function Analysis (DFA) using surface morphometrics. This DFA produced a predictive linear function for categorizing wrinkle ridges and lobate scarps and for quantifying which landforms were exemplars within those categories. The three most influential variables on the surface morphometry DFA were the maximum width, forelimb slope, and back limb length. We then modeled the subsurface structural geology of 50 landforms using MOVE Structural Geology Modeling Software and conducted a second DFA based on subsurface metrics. DFA was most influenced by the dip and depth of the lower ramp base. When both surface morphology and subsurface geometry are input into single DFA, wrinkle ridges and lobate scarps can be distinguished quantitatively 96% of the time. Our results also show that lobate scarps accommodate more strain and imply that studies should consider landform type when interpreting local, regional, and global geological stress histories.

Damage mechanism identification and failure behavior of 2D needle-punched SiCf/SiC composites based on acoustic emission and digital image correlation

In order to improve the reliability of damage analysis for SiCf/SiC composites, an identification method of damage mechanism was established by combining in-situ acoustic emission (AE) and digital image correlation (DIC). The corresponding failure behavior of 2D needle-punched SiCf/SiC composites during ambient-temperature tensile test was investigated in detail. Through a machine learning k-means algorithm, AE signals could be effectively divided into five clusters: friction and sliding, interface damage, matrix cracking, individual fiber breaks and collective fiber breaks. DIC results show that the surface strain of composites increased non-uniformly during the tensile process, and the architecture of the composites had a significant influence on the initiation and propagation of cracks. To summarize, the tensile process consisted of three stages: the elastic stage, the rapid propagation of matrix cracks, the coordinated fiber fracture within the large strain bands. The failure of composites was dominated by the limited load transferring ability of the interface.

Contemporary crustal strain rates derived from GPS measurements in southwestern China

Surface strain rates in southwestern China can provide constraints on tectonic evolution of the Tibetan Plateau. Unfortunately, different strain rate fields were obtained from different authors although almost the same GPS data were exploited. Based on updated GPS data, in this paper, we calculate the strain rates in southwestern China using the method proposed by Zhu et al. (2005, 2006). The results confirm that the strain rates in the Sichuan Basin and the South China Block are very small, and the high values are largely concentrated along the Xianshuihe-Anninghe-Xiaojiang fault system and the Sagaing Fault. Furthermore, the highest principal strain rates are located around the eastern Himalayan syntaxis (EHS), with compressive orientations perpendicular to the strike of the Main Thrust Belt. The basic characteristic of the strain rate distribution is in accordance with the tectonic structures from the geological and geophysical investigations. In particular, the two calculated extensive deformation regions basically match the locations of normal-faulting earthquakes in the Sichuan-Yunnan Rhombic Block (SYRB), with one in N-S extension trending in the northern SYRB, and the other nearly E-W orientation in the southern SYRB. We suggest that the extensive deformation and the normal faulting earthquakes in southwestern China is mainly controlled by the lower crustal channel flow with a bend direction, rather than by gravitational spreading alone, as previous authors proposed.

Surface chemo-mechanics coupling of MnO2/Au layered composites under electrochemical environment

The intersection of surface mechanics and electrochemistry has gradually become a prominent topic in the realm of new energy research. To explore the influence of the electrochemical process on the stress of energy storage electrode composite, supercapacitor material manganese dioxide (MnO2) was selected as the coating and the MnO2/Au composites were prepared by the electrochemical deposition. The surface stress of MnO2/Au composites under different electrochemical modes and the stress variation law of MnO2 with varying thicknesses were determined. The addition of MnO2 could alter the stress response and the strain magnitude of the gold electrode with varied electrochemical potential. The reversible tensile strain within the Au surface during 0.3 ∼ 0.8 V charging was induced by the absorption of SO42−, while the compressive strain of the MnO2/Au composites was related to the extraction of Na+ ions resulting from the redox pseudocapacitance of MnO2. Notably, the produced stress exhibited a linear correlation with the capacitance. And the long-cycle tests revealed that as the specific capacitance of electrodes decreased, the induced tensile stress progressively diminished. This study emphasized the surface chemo-mechanics coupling of both the Au layer and MnO2/Au composites, which would provide a new approach to regulating surface strain in the solid–liquid interface.

Identification of hardening and fracture behaviors of titanium alloy by a hybrid digital image correlation and finite element method

The reliable identification of deformation and fracture behaviors of titanium alloys is essential for accurate numerical simulation in sheet metal forming, cutting process and crash. In this study, an inverse method is proposed to identify both strain hardening and fracture behavior of titanium alloys by a hybrid experimental-finite element analysis. Uniaxial and notched tensile specimens are tested on the additively manufactured and cold rolled sheet Ti6Al4V alloys. The distributions of displacement and strain on the specimen surface during the loading are measured by digital image correlation method. An identification strategy, considering the stress–strain curve, surface strain evolution and variation of specimen width, is proposed to identify the strain hardening model parameters at large strain range. Finite element simulations are performed to update the model parameters by using the iterative inverse method. The parameters of fracture model are determined through experiments on tensile specimens in combination with numerical simulation. The experimental and simulation results show the feasibility and effectiveness of the proposed identification method, that it can be further used to characterize the plastic and fracture behaviors of other metallic materials in practice.