Metals In Samples Research Articles

Bending moment calibration for rotational bending fatigue testing machine based on strain measurement

Abstract Rotational bending fatigue testing is an important method to evaluate the fatigue of metal materials under cyclic loading. Specifically, the fatigue strength is evaluated through repeated rotational bending under complex loads with the accuracy affected by the bending moment. Here, a method based on strain measurements is proposed for calibrating the bending moment of rotational bending fatigue testing machines. Specifically, the strain of a metal sample under loading with resistance strain gauges was recorded using a strain acquisition system to measure the bending moment. The positions of strain gauges were designed according to the principle of strain measurements to establish a calibration program. Three metal samples of different sizes were tested on two types of rotational bending fatigue testing machines, and the measurement uncertainty was evaluated and verified. The experimental results showed that the proposed method measured and calibrated the bending moment of rotational bending fatigue testing machines rapidly, conveniently, and accurately. The results also provide a practical reference for research and application in related fields.

Evaluation of Health Risk and Heavy Metal Pollution Caused by Dust Storms in Zabol City.

This study investigated the concentrations and compositions of specific elements in total suspended particulate (TSP) samples and the associated ecological, carcinogenic, and non-carcinogenic risks related to the inhalation, ingestion, and dermal absorption of heavy metals. The study focused on adult and pediatric populations in the highly dust-polluted city of Zabol, Iran, during 2022-2023. The samples were analyzed by using inductively coupled plasma optical emission spectrometry (ICP-OES). The concentration of metals in milligram per kilogram (mg/kg) was as follows: Al (75053) > Ca (8206) > Fe (5439) > Mg (5323) > Zn (15.27) > Pb (3.66) > Cr (3.38) > Cd (0.011); according to the results, the highest amount of metals related to aluminum and calcium in dust particles. The calculated individual indices, including the ecological risk index (ERI), pollution factor (Cfi), and geographic accumulation index (Igeo), indicated that calcium exhibited minimal pollution, while the metal samples (Al, Mg, Fe, Cd, Cr, Pb, and Zn) were categorized as uncontaminated. The results revealed that the ecological risk factor (Er) is below 40, indicating a low level of contamination. Additionally, the pollution level determined by the ecological risk potential (RI) was less than 150, suggesting a low probability of contamination. Ingestion posed the highest average hazard quotient (HQ) values for both children and adults in terms of non-carcinogenic risk assessment, while cutaneous and inhalation exposures showed lower values. Furthermore, the hazard index (HI) for heavy metals remained below the safe threshold of 1. The risk index (RI) values for lead, cadmium, and chromium were all below 1 × 10-6 in both adult and pediatric populations. The United States Environmental Protection Agency (USEPA) guidelines suggest an acceptable level of carcinogenicity for all heavy metals, indicating a potential risk of cancer associated with the presence of these metals in suspended particles in Zabol.

Human Health Risk Assessment and Water Quality Index of piped water supply system in Gulshan-e-Iqbal Town, Karachi (A Preliminary Town level study).

In the present study, piped water samples from Gulshan-e-Iqbal Town, Karachi, were evaluated for their Health Risk Assessment (HRA) and Water Quality Index (WQI). For this, different physicochemical and microbiological parameters were analyzed, and the results were evaluated according to the guidelines established by the WHO (2011) and the National Standards for Drinking Water Quality (NSDWQ) (2008). With the exception of sulphate, all physicochemical parameters were well within the guideline values. The mean concentrations of the metals in the samples were in the following order: Ca2+ > Mg2+ > Zn > Fe > Pb > Ni > Cr > As. More than 70% of the samples tested for Total Coliform Count (TCC), Total Faecal Coliform Count (TFC), Total Feacal Streptococci (TFS), and Total Aerobic Count (TAC) were feacal contaminated. E. coli was also isolated in almost 84.61% of the tested piped water samples. Results from the WQI revealed that 95.6% of samples had good physico-chemical characteristics, and 26% of the piped water samples had good microbiological quality. The WQI readings of all the samples for metals showed that they were unfit for human consumption. The mean Chronic Daily Intake (CDI) and Hazard Quotient (HQ) values, respectively, were in the following order: Zn > Fe > Pb > Ni > Cr > As, and Pb > As > Ni > Cr > Zn > Fe. All HQ values for As and Pb were greater than 1, and 50% of piped water samples had an HQ value for Ni that was greater than 1, indicating that people may suffer serious health issues as a result. All of the piped water samples except the area of block 13 D (S-5), had HQ values of less than 1 in relation to iron, but Zn HQ values of less than 1 indicated only mild health problems. Discharge of untreated sewage and cross-contamination are all potential sources of contamination that could result in diseases that are harmful to the public's health. Water monitoring and management projects should be implemented in order to improve pipeline infrastructure and reduce sewage leakages.

Design and implementation of a nondestructive testing system for magnetic field imaging based on machine learning

This study presents the design of a nondestructive testing (NDT) system for detecting metal defects using a magnetic field sensor array. The system integrates a hardware-software detection framework that includes parallel computation and processing cores, along with multiple anisotropic magnetoresistance (AMR) sensors. These AMR sensors capture subtle variations in the magnetic field, which serve as the foundation for defect identification. The system enables synchronized data acquisition from multiple AMR sensors, achieving multi-axis data fusion and parallel signal processing. Furthermore, the detection system gathers defect features to train an NDT system based on machine learning (ML). Subsequently, ML-generated defect imaging features are processed through an imaging framework, producing magnetic field imaging (MFI) for precise defect localization. The study tested six different metal samples with various defect sizes and types to validate the system. The results demonstrate the system’s ability to accurately detect and identify different defects, highlighting the high precision of magnetic field detection and the overall effectiveness of the proposed system for NDT.

Experimental determination of tin partitioning between titanite, ilmenite, and granitic melts using improved capsule designs

Abstract Investigating mineral/melt Sn partitioning at high temperatures and pressures is a difficult task because Sn is a redox-sensitive multivalent element and easily alloys with noble metal sample capsules. To obtain accurate Sn partition coefficients between titanite, ilmenite, and granitic melts, we developed single capsule Pt or Au and double capsule Pt95Rh5 (or Au)-Re designs to avoid significant Sn loss at a controlled oxygen fugacity (fO2). With these new capsule designs, we performed piston-cylinder experiments of Sn partitioning between titanite, ilmenite, and granitic melts. The experimental P-T-fO2 conditions were 0.5–1.0 GPa, 850–1000 °C, and ~QFM+8 to ~QFM-4 (quartz-fayalite-magnetite, QFM, buffer), with fO2 controlled by the solid buffers of Ru-RuO2, Re-ReO2, Co-CoO, graphite, and Fe-FeO. The obtained mineral/melt Sn partition coefficients (DSnmin/melt) are 0.48–184.75 for titanite and 0.03–69.45 for ilmenite at the experimental conditions. The DSnmin/melt values are largely dependent on fO2, although the effects of temperature and melt composition are also observed. DSnTtn/melt strongly decreases with decreasing fO2, from ~46–185 at the most oxidizing conditions (Ru-RuO2 buffer), to ~2–16 at moderately oxidizing to moderately reducing conditions (Re-ReO2 to Co-CoO and graphite buffers), to <1 at the most reducing conditions (Fe-FeO buffer). DSnIlm/melt exhibits a variation trend similar to DSnTtn/melt but is always lower than DSnTtn/melt at a given fO2. These DSnmin/melt values can be applied to quantitatively assess the mineralization potential of granitic magmas. Using DSnTtn/melt, we estimate that Sn contents are ~150–400 ppm in the pre-mineralization magmas of the tin-mineralized Qitianling plutons (South China).

Determination of trace analytes in nuclear grade Calcium Metal Samples by Axially Viewed Inductively Coupled Plasma – Atomic Emission Spectrometric technique

An Inductively Coupled Plasma – Atomic Emission Spectrometric (ICP-AES) method has been developed for the direct determination of 19 analytes namely, Al, B, Be, Cd, Co, Cr, Cu, Fe, Li, Mg, Mo, Mn, Ni, Pb, Pd, Si, Ta, V and W at trace concentration levels in calcium matrix. In nuclear industry, quality control and assurance of nuclear fuels and associated materials for trace metallic impurity contents form an integral part of the system for the smooth functioning of the reactor for the stipulated time span. In this context, it was required to determine trace analytes in nuclear grade Calcium which is used as a reducing agent for the production of U, Th, Pu, etc. in nuclear industry. Using axial ICP-AES, initially calibration curve for Ca with 396.847nm analytical line was obtained. Systematic studies were carried out to identify various analytical wavelengths of the analyte elements which are almost free from Ca, being the main matrix and calibration curves were obtained. For all analytes and Ca, detection limits and sensitivity values were calculated. To validate the method, three synthetic samples with analyte contents in the range of 0.1 - 5 g/mL and Ca at 1 mg/mL were analyzed, the % recovery being in the range of 80-120% with precision better than 5% RSD. The method was found to be useful for the direct determination of the elements of interest in calcium matrix and was applied for the analysis of two nuclear grade real life calcium metal samples.

Adaptive Threshold Algorithm for Outlier Elimination in 3D Topography Data of Metal Additive Manufactured Surfaces Obtained from Focus Variation Microscopy

The topography of surfaces produced by metal additive manufacturing is a challenge for optical measurement systems such as focus variation microscopes. These irregularities can lead to artifacts, such as incorrectly measured protrusions or spikes, hampering reliable topographic characterization. In order to eliminate this problem, we introduce a new algorithm based on dual convolving a vertical Sobel operator with cross sections of an image stack parallel to the scanning direction of the so-called depth scan. This has proven beneficial in order to distinguish the focus region from out-of-focus areas where outliers are frequently detected. This paper introduces a method for deriving self-adaptive thresholds from the convolution result and compares the effects of different operators in creating self-adaptive thresholds. Additionally, a simulation model of focus variation microscopy is introduced to validate both the measuring system and the proposed algorithm, thereby enhancing the overall performance of focus variation microscopy. Finally, comparisons of measurement results on rough metal additive manufacturing workpieces with and without self-adaptive thresholds are discussed to demonstrate the algorithm’s effectiveness.The utilization of self-adaptive thresholds demonstrably reduces the uncertainty range in roughness parameter calculations. For example, in the case of an additive manufactured metal sample due to outlier elimination, the Sz roughness value reduces from 543 µm to 413 µm.

Effects of Hydrogen Dissociation During Gas Flooding on Formation of Metal Hydride Cluster Ions in Secondary Ion Mass Spectrometry.

The application of hydrogen flooding was recently shown to be a simple and effective approach for improved layer differentiation and interface determination during secondary ion mass spectrometry (SIMS) depth profiling of thin films, as well as an approach with potential in the field of quantitative SIMS analyses. To study the effects of hydrogen further, flooding of H2 molecules was compared to reactions with atomic H on samples of pure metals and their alloys. H2 was introduced into the analytical chamber via a capillary, which was heated to approximately 2200 K to achieve dissociation. Dissociation of H2 up to 30% resulted in a significant increase in the intensity of the metal hydride cluster secondary ions originating from the metallic samples. Comparison of the time scales of possible processes provided insight into the mechanism of hydride cluster secondary ion formation. Cluster ions presumably form during the recombination of the atoms and molecules from the sample and atoms and molecules adsorbed from the gas. This process occurs on the surface or just above it during the sputtering process. These findings coincide with those of previous mechanistic and computational studies.

An Assessment of the Presence of Clostridium tetani in the Soil and on Other Surfaces

Introduction: Standard emergency medicine practice includes tetanus vaccine administration as part of wound care management for patients who are not fully immunized. Since there have been no available studies in the United States reaffirming the prevalence of Clostridium tetani (C tetani) since 1926, we sought to identify its prevalence in a major urban county in the US. Methods: We sampled soil, rusted metal, concrete, and dog feces to determine the prevalence of C tetani in a single metropolitan county in the United States. Soil samples and swabs were collected from four locations: the soil of a public park and an elementary school; dog feces from a single public dog park; and rusted surfaces (metal and concrete) in common student areas of a university campus. The presence of C tetani in each sample was determined using a quantitative polymerase chain reaction. Results: In total, 200 samples were collected, of which 37 (18.5%) tested positive for C tetani DNA. Among the 140 samples taken from the soil, just one (0.7%) tested positive for C tetani DNA. Of the 40 samples of rusted metal and concrete surfaces, 30 (75%) tested positive for C tetani, and six (30%) of the 20 samples from dog feces tested positive for C tetani. Conclusion: We found that C tetani is frequently present on rusted metal and concrete surfaces but rarely in soil samples. Minor wounds contaminated with soil may be considered low risk for tetanus. However, future studies should assess the burden of C tetani in other similar urban, suburban, and rural environments to help determine the threat of C tetani more exactly.

Immobilization of Cadmium Via Ureolytic Bacteria Isolated from Greywater Waste and Horse Faeces

With the constant growth of technology and pollution caused by urban expansion, heavy metal contamination has become an alarming concern. The performance of Microbial induced carbonate precipitation technology in immobilizing heavy metal has been demonstrated by several researchers. While various studies have successfully isolated ureolytic bacteria from a variety of sources, there are very limited studies that have focused on isolating them from local waste sources, specifically Greywater and Horse Faeces for MICP application, which benefits in terms of economical, sustainability, and efficiency for engineering purposes. The study aims to investigate the effect of urease-producing bacteria derived from Greywater and horse faeces on heavy metal immobilization. The methods include collecting waste samples, isolating and subculturing of ureolytic bacteria, testing the physiological characteristics of ureolytic bacteria, examining the tolerance test and evaluating heavy metal removal efficacy through Atomic Absorption Spectrophotometry (AAS) analysis, and last but not least, Scanning Electron Microscopy (SEM) and Energy-Dispersive X-ray (EDX) analyses of morphological and mineralogical properties of biominerals formed after heavy metal immobilization treatment. The study found that bacteria from Greywater were more effective at heavy metal immobilization than those from Horse Faeces. Additionally, AAS analysis indicates the greywater-derived bacteria from the residential area sample's exceptional competence in Cd2+ removal, with a significant 80.19% removal rate exceeding the horse faeces bacteria sample's removal rate of 65.26%. The morphological analysis confirmed the presence of heavy metal carbonate in treated heavy metal samples, as well as presenting insight into the effectiveness and application of local ureolytic bacteria's potential for heavy metal toxicity degradation.

A tracer-free photographic method for the estimation of the velocity field in a liquid metal pool

Abstract Accurately measuring the velocity field (VF) of liquid metals is essential for optimizing and controlling high-temperature industrial processes, yet remains a challenging task despite the numerous existing velocimetry techniques. In this paper, a methodology for estimating the VF of a liquid metal pool is proposed. The experimental set-up used here to heat the metal sample up to the liquid state and collect data is presented. This set-up primarly intented to perform flash experimetns on liquid metals, allows contactless heating and data measurements by a high speed camera. The proposed methodology for estimating the VF consists then in implementing a Non-Rigid Registration between the different frames of the recorded temperature fields (TFs). This method is applied on TFs resulting from multiple experimental tests conducted on iron samples in the temperature range of 1 850 − 2 100 K. The consistency of the results is put to test via multiple validation tests. The influence of the main parameters is also evaluated. The results show that the proposed methodology allows a fine experimental quantification of liquid metal VFs with an estimated error of 8 % and confirm the feasibility of the proposed approach.

Characterization of novel 3D-printed metal shielding for brachytherapy applicators.

To characterize 3D-printed stainless steel metal samples in the presence of an Iridium-192 source for organ-at-risk sparing in gynecologic brachytherapy. Samples of 3D-printed stainless steel (5.5×5.5 cm2, thickness range 1-5mm) were embedded in a solid water phantom at varying distances from source catheters. An Ir-192 brachytherapy source was passed through the phantom and the dose was measured using EBT3 Gafchromic film. The film was initially positioned in the sagittal plane 2cm away from the catheters, with the metal directly below and then 1cm from the film. A uniform dose was delivered at the film plane. A second setup measured a depth dose curve in solid water with film in the transverse plane directly above the metal samples. This setup was recreated using Monte Carlo simulations (EGSnrc egs_brachy). Validation between methods was performed with unshielded (solid water only) measurements. The planar dose passing through the metal samples (thickness 1-5mm) at the midpoint between the film and catheters, decreased compared to solid water by 7.4%±6.9% to 26.5%±5.5%. Dose enhancement on the order of 5% was noted when metal was directly adjacent to the film. The average decrease in depth dose from a single dwell position ranged from 10.0%±5.9% (1mm) to 21.1%±5.3% (5mm) as measured with film, and from 3.8%±0.9% (1mm) to 16.3%±0.9% (5mm) using MC simulation. The average depth dose values were measured using a line width of 2.5mm for film, and 3mm for MC simulation, and the measurements generally agree within standard error. The 3D-printed metal samples show potential for personalized applicators. Maximum dose reduction of 26.5%±5.5% compared to solid water was measured at 2cm from the source using the 5mm sample. An outer layer of solid water could potentially be used to reduce dose enhancement due to increased scatter near the metal.

In the LiCl-KCl melt at 500<sup>о</sup>С depending on the content of Li<sub>2</sub>О и LiOH

Molten alkali metal chlorides used in pyrotechnologies are aggressive corrosive agents. The high operating temperature of the process, the heterogeneity of the environment, and the significant corrosion activity of the molten salt necessitate both the search for stable structural materials and the development of methods for protecting the structural elements of high-temperature technological devices. Corrosion loss reduction techniques traditionally used in low temperature environments are not applicable at high temperatures. The article examines the influence of oxygen-containing impurities (lithium oxide and hydroxide) on the corrosion behavior of metallic nickel (grade NP1) – the main component of candidate structural alloys, a thermodynamically and structurally stable material in the melt for the process of electrolytic refining of spent nuclear fuel. A method for preparing the LiCl–KCl salt electrolyte and obtaining lithium oxide by thermal decomposition of anhydrous lithium hydroxide under vacuum is described, and the concentrations of impurities in the electrolyte and the synthesized lithium oxide are determined. An installation for conducting corrosion tests in an inert atmosphere of a glove box is presented. To assess the corrosion resistance of the material, the following were used: gravimetric analysis, X-ray diffraction analysis of the surface and cross-sectional sections, and X-ray diffraction analysis of the surface of the samples. The dependences of the corrosion rate of the material on the concentration of oxygen-containing additives Li2O and LiOH were obtained. Based on a combination of gravimetric, X-ray microspectral and X-ray phase analysis data, it was established that metallic nickel samples demonstrate high corrosion resistance in the studied melts with the introduction of Li2O and LiOH additives.

Detection and Prediction of Toxic Aluminum Concentrations in High-Priority Salmon Rivers in Nova Scotia.

Elevated concentrations of toxic cationic aluminum (Ali) are symptomatic of terrestrial and freshwater acidification and are particularly toxic to salmonid fish species such as Atlantic salmon (Salmo salar). Speciated metal samples are rarely included in standard water monitoring protocols, and therefore the processes affecting Ali dynamics in freshwater remain poorly understood. Previous analysis of Ali concentrations in Nova Scotia (Canada) rivers found that the majority of study rivers had concentrations exceeding the threshold for aquatic health, but a wide-scale survey of Ali in Nova Scotia has not taken place since 2006 (Dennis, I. F., & Clair, T. A., 2012, Canadian Journal of Fisheries and Aquatic Sciences, 69(7), 1174-1183). The observed levels of dissolved aluminum in Atlantic salmon (Salmo salar) rivers of Atlantic Canada have potential serious and harmful effects for aquatic populations. We present the findings of the first large-scale assessment of the Ali status of Nova Scotia rivers in 17 years; we measured Ali concentrations and other water chemistry parameters at 150 sites throughout the Southern Uplands region of Nova Scotia from 2015 to 2022. We found that Ali concentrations exceeded toxic thresholds at least once during the study period at 80% of the study sites and that Ali concentrations increased during the study period at all four large-sample study sites. Modeling of relationships between Ali concentrations and other water chemistry parameters showed that the most important predictors of Ali are concentrations of the dissolved fractions of Al, iron, titanium, and calcium, as well as dissolved organic carbon and fluoride. We developed a fully Bayesian linear mixed model to predict Ali concentrations from a test data set within 15 μg/L. This model may be a valuable tool to predict Ali concentrations in rivers and to prioritize areas where Ali should be monitored. Environ Toxicol Chem 2024;00:1-12. © 2024 The Author(s). Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Identification of corrosion nature using acoustic emission in representative scale samples

Monitoring corrosion is critically important across numerous applications, given its occurrence in key industrial sectors such as energy production, transportation, and civil engineering to prevent leaks and failures. Especially, determining the exact nature of corrosion phenomena could help planning specific maintenance operations, reducing costs and risks. Machine Learning methods have demonstrated capacities to discriminate corrosion phenomenona. An important step to create precise Machine Learning models is the quality of training datasets. With this goal in mind, this paper presents experiments performed on different metallic samples to create specific corrosion forms, respectively pitting and uniform corrosion to train a supervised model. This model is evaluated on 316L steel samples prone to endure both pitting and uniform corrosion. The usage of supervised learning is then discussed compared to other methods.

ANALYSIS OF THE QUALITY OF THE RESTORED GEAR TOOTH OF LARGE-MODULE GEARS

This study examines the quality of a gear tooth surface fragment restored through electric arc welding. Visual inspection revealed a defect-free, dense surface. Macrostructure examination displayed uniformity and absence of cracks in the metal sample. The high hardness (HRC-36.61) of the weld deposit is crucial for wear resistance, while the base metal, with lower hardness (HRC-29.09), ensures ductility and impact toughness. Martensitic and residual austenitic structures in the weld deposit indicate deformation-resistant properties, with austenite providing good ductility and martensite contributing to high hardness and strength, making the material resistant to wear and deformation under dynamic loads. Thin lens-like martensitic plates and a reed-like structure suggest unique formation characteristics during electroslag welding’s oxidizing-reducing reactions. Microstructure analysis revealed a finer structure in the weld deposit compared to the base metal. The base metal exhibited a ferrite-pearlite structure typical of many steels, unchanged after welding. The weld deposit showed elevated carbon (0.70 %) and manganese (1.38 %) concentrations, typical for weld deposits, influencing mechanical properties. Elements like manganese and molybdenum enhance wear resistance, while the presence of chromium (0.42 %) and nickel (0.12 %) improves corrosion resistance, crucial in aggressive environments. Keywords: large-module gears, tooth wear, electro slag surfacing, hardness, analysis

Evaluation of a Metal Artifact Reduction Algorithm for Image Reconstruction on a Novel CBCT Platform.

The presence of metal implants can produce artifacts and distort Hounsfield units (HU) in patient computed tomography (CT) images. The purpose of this work was to characterize a novel metal artifact reduction (MAR) algorithm for reconstruction of CBCT images obtained by the HyperSight imaging system. Three tissue-equivalent phantoms were fitted with materials commonly used in medical applications. The first consisted of a variety of metal samples centered within a solid water block, the second was an Advanced Electron Density phantom with metal rods, and the third consisted of hip prostheses positioned within a water tank. CBCT images of all phantoms were acquired and reconstructed using the MAR and iCBCT Acuros algorithms on the HyperSight system. The signal-to-noise ratio (SNR), artifact index (AI), structural similarity index measure (SSIM), peak signal-to-noise ratio (PSNR), and mean-square error (MSE) were computed to assess the image quality in comparison to artifact-free reference images. The mean HU at various VOI positions around the cavity was calculated to evaluate the artifact dependence on distance and angle from the center of the cavity. The artifact volume of the phantom (excluding the cavity) was estimated by summing the volume of all voxels with HU values outside the 5th and 95th percentiles of the phantom CBCT with no artifact. The SNR, AI, SSIM, PSNR, and MSE metrics demonstrated significantly higher similarity to baseline when using MAR compared to iCBCT Acuros for all high-density materials, except for aluminum. Mean HU returned to expected solid water background at a shorter distance from metal sample in the MAR images, and the standard deviation remained lower for the MAR images at all distances from the insert. The artifact volume decreased using the novel MAR algorithm for all metal samples excluding aluminum (p<0.001) and all hip prostheses (p<0.05). Varian's HyperSight MAR reconstruction algorithm shows a reduction in metal artifact metrics, motivating the use of MAR reconstruction for patients with metal implants.

Effects of plasma electrolytic polishing on the surface and mechanical properties of Ti-6.5Al-3.5Mo-1.5Zr-0.3Si specimen fabricated by laser powder bed fusion

The high roughness of titanium alloy specimen fabricated by laser powder bed fusion (LPBF) may limit the application of LPBF technology. Plasma electrolytic polishing (PEP) can effectively reduce the surface roughness of metal samples. In this study, an orthogonal test was designed to investigate the effects of polishing time, voltage and electrolyte temperature on the reduction of roughness and wall thickness of Ti-6.5Al-3.5Mo-1.5Zr-0.3Si specimens fabricated by LPBF. The surface roughness of the specimen decreased from Ra = 49.1 μm to Ra = 9.1 μm and the thickness decreased from 1.72 mm to 1.38 mm after the PEP. Due to the recoil pressure induced by rupture of vapor-gaseous envelope (VGE) and the annealing effect caused by electron impact, the width of α/α' grains on the surface of TC11 specimen decreased from 0.51 μm to 0.46 μm; the mean value of geometrically necessary dislocations (GND) increased by 9.8 %; the proportion of high angle grain boundaries (HAGBs) increased from 75.2 % to 80.8 %; the proportion of twin grain boundary length increased from 2.9 % to 11.9 %, and the activated twin variant type increased from 2 to 4. The number of pores in the samples reduced from 85 to 2 after PEP, which resulted in the improvement of tensile and fatigue properties. The ultimate strength and elongation of the tensile specimens increased by 6.2 % and 53.5 % respectively. The infinite fatigue life maximum stress of the high cycle fatigue specimen increased by 62.5 %. Another reason for the improvement of mechanical properties may be the self-healing of microcracks and the electroplasticity in the specimens.

The Effect of Relative Humidity in Conductive Atomic Force Microscopy.

Conductive atomic force microscopy (CAFM) analyzes electronic phenomena in materials and devices with nanoscale lateral resolution, and it is widely used by companies, research institutions, and universities. Most data published in the field of CAFM is collected in air at a relative humidity (RH) of 30-60%. However, the effect of RH in CAFM remains unclear becauseprevious studies often made contradictory claims, plus the number of samples and locations tested is scarce. Moreover, previous studies on this topic didnot apply current limitations, which can degrade the CAFM tips and generate false data. This article systematically analyzes the effect of RH in CAFM by applying ramped voltage stresses at over 17,000 locations on ten different samples (insulating, semiconducting, and conducting) under seven different RH. An ultra-reliable setup with a 110-pA current limitation during electrical stresses is employed, andexcellent CAFM tip integrity after thousands of tests is demonstrated. It is found that higher RH results in increased currents due to the presence of a conductivewater meniscus at the tip/sample junction, which increases the effective area forelectron flow. This trend is observed in insulators and ultra-thin semiconductors; however, in thicker semiconductors the electron mean free path is high enough to mask this effect. Metallic samples show no dependence on RH. This study clarifies the effect of relative humidity in CAFM, enhances understanding of the technique, and teaches researchers how to improve the reliability of their studies in this field.

Experimental investigation of stick-slip behaviors in dry sliding friction

Friction-induced vibration, particularly the bothersome stick-slip behavior, is a significant contributor to machine damage and component failure. In this study, the vibrational displacement, sound pressure, and coefficient of friction (COF) of several metal or alloy samples in dry conditions are tested using a reciprocating friction force test apparatus. It is found that the stick-slip behavior is more likely to occur at low sliding speeds and high normal loads. Furthermore, under the same working conditions, increasing the surface roughness of the sample or enhancing the hardness difference between the sample and the counterpart can mitigate the stick-slip behavior during the friction process. By analyzing the characteristic parameters of the stick-slip behavior, it is found that the temporal period and the stick-time decrease significantly with an increase in relative sliding speed. Additionally, the amplitude and intensity of the friction-induced noise increases with the increase of the relative sliding speed and normal load. The frequencies of the sound pressure are primarily concentrated around the natural frequency of the frictional system. Finally, we extract the COF and find that the average COF as well as the maximum and minimum COF first decreases sharply, and then becomes stable with the increase of the relative sliding speed due to the transition of friction state from stick-slip behavior to smooth sliding.