Material Characterization Techniques Research Articles

Adaptable physics-based super-resolution for electron backscatter diffraction maps

In computer vision, single-image super-resolution (SISR) has been extensively explored using convolutional neural networks (CNNs) on optical images, but images outside this domain, such as those from scientific experiments, are not well investigated. Experimental data is often gathered using non-optical methods, which alters the metrics for image quality. One such example is electron backscatter diffraction (EBSD), a materials characterization technique that maps crystal arrangement in solid materials, which provides insight into processing, structure, and property relationships. We present a broadly adaptable approach for applying state-of-art SISR networks to generate super-resolved EBSD orientation maps. This approach includes quaternion-based orientation recognition, loss functions that consider rotational effects and crystallographic symmetry, and an inference pipeline to convert network output into established visualization formats for EBSD maps. The ability to generate physically accurate, high-resolution EBSD maps with super-resolution enables high-throughput characterization and broadens the capture capabilities for three-dimensional experimental EBSD datasets.

Effect of Electron and Proton Irradiation on Structural and Electronic Properties of Carbon Nanowalls.

In this work, a complex experimental study of the effect of electron and proton ionizing radiation on the properties of carbon nanowalls (CNWs) is carried out using various state-of-the-art materials characterization techniques. CNW layers on quartz substrates were exposed to 5 MeV electron and 1.8 MeV proton irradiation with accumulated fluences of 7 × 1013 e/cm2 and 1012 p/cm2, respectively. It is found that depending on the type of irradiation (electron or proton), the morphology and structural properties of CNWs change; in particular, the wall density decreases, and the sp2 hybridization component increases. The morphological and structural changes in turn lead to changes in the electronic, optical, and electrical characteristics of the material, in particular, change in the work function, improvement in optical transmission, an increase in the surface resistance, and a decrease in the specific conductivity of the CNW films. Lastly, this study highlights the potential of CNWs as nanostructured functional materials for novel high-performance radiation-resistant electronic and optoelectronic devices.

Effectiveness of the analytical models used in standard techniques for mechanical property characterization of 2D materials

Two dimensional (2D) materials are usually assumed to be continuum thin films to study their mechanical behavior. Freestanding indentation testing and pressure bulge testing are two standard techniques for characterizing the mechanical properties of thin films. Compared with the former, the latter is far less often used to characterize the elastic moduli of 2D materials, even though there is no solid evidence to show that the former is more effective than the latter. In the present work, the effectiveness of the analytical models adopted in both approaches on determining the elastic moduli of 2D materials are investigated using numerical analysis, which can be evaluated based upon the accuracy of the determined elastic moduli, and the effects of Poisson’s ratio and the applied loading range are also considered. To account for the effect of the adhesive boundary condition of freestanding 2D materials in the testing, the numerical simulations of the initially unstressed samples, pre-stretched samples and slack samples are all analyzed in the present work. It is found that the bulge testing model is actually more effective than the indentation model on determining the mechanical properties of 2D materials.

Microstructural defects governing torsional fatigue failure of additively manufactured as-built and heat-treated Inconel 718

Nickel-based superalloys, such as Inconel 718 (IN718), have the unique properties of high strength, oxidation, and corrosion resistance, hence necessitating their wide use in aircraft engine structural components, power-generation engines, pressure vessels, high performance automobiles, and rocket engines. Additive manufacturing (AM) of these metal superalloys is an emerging technology, which is being investigated in its capability in driving material microstructural development towards enhanced mechanical performance. With torsional fatigue as an often underlying cause for failure of components within these applications, this study investigates the microstructural defects induced through the additive manufacturing process that have driven Inconel 718 samples to failure when subjected to torsional fatigue loading conditions. As-built and heat-treated Inconel 718 torsional fatigue fracture surfaces were compared through use of a variety of material characterization techniques, to show similarities, or lack thereof, in the defects formed due to the AM process that have contributed to torsional fatigue fracture. Results from both as-built and heat-treated direct metal-laser sintered (DMLS) Inconel 718, manufactured using optimized processing parameters reveal that primary torsional fatigue cracks initiated at surface and sub-surface defects where lack of fusion regions and un-melted powder particles are apparent. Through these analyses, a correlation was made between the fracture mechanics response exhibited by each build orientation/post-processing condition and resulting torsional fatigue properties.

Three-Dimensional Graphene-TiO2-SnO2 Ternary Nanocomposites for High-Performance Asymmetric Supercapacitors.

Ternary nanocomposites synergistically combine the material characteristics of three materials, altering the desired charge storage properties such as electrical conductivity, redox states, and surface area. Therefore, to improve the energy synergistic of SnO2, TiO2, and three-dimensional graphene, herein, we report a facile hydrothermal technique to synthesize a ternary nanocomposite of three-dimensional graphene-tin oxide-titanium dioxide (3DG-SnO2-TiO2). The synthesized ternary nanocomposite was characterized using material characterization techniques such as XRD, Raman spectroscopy, FTIR spectroscopy, FESEM, and EDXS. The surface area and porosity of the material were studied using Brunauer-Emmett-Teller (BET) studies. XRD studies showed the crystalline nature of the characteristic peaks of the individual materials, and FESEM studies revealed the deposition of SnO2-TiO2 on 3DG. The BET results show that incorporating 3DG into the SnO2-TiO2 binary nanocomposite increased its surface area compared to the binary composite. A three-electrode system compared the electrochemical performances of both the binary and ternary composites as a battery-type supercapacitor electrode in different molar KOH (1, 3, and 6 M) electrolytes. It was determined that the ternary nanocomposite electrode in 6 M KOH delivered a maximum specific capacitance of 232.7 C g-1 at 1 A g-1. An asymmetric supercapacitor (ASC) was fabricated based on 3DG-SnO2-TiO2 as a positive electrode and commercial activated carbon as a negative electrode (3DG-SnO2-TiO2//AC). The ASC delivered a maximum energy density of 28.6 Wh kg-1 at a power density of 367.7 W kg-1. Furthermore, the device delivered a superior cycling stability of ∼97% after 5000 cycles, showing its prospects as a commercial ASC electrode.

Experimental realization of neutron helical waves.

Methods of preparation and analysis of structured waves of light, electrons, and atoms have been advancing rapidly. Despite the proven power of neutrons for material characterization and studies of fundamental physics, neutron science has not been able to fully integrate these techniques because of small transverse coherence lengths, the relatively poor resolution of spatial detectors, and low fluence rates. Here, we demonstrate methods that are practical with the existing technologies and show the experimental achievement of neutron helical wavefronts that carry well-defined orbital angular momentum values. We discuss possible applications and extensions to spin-orbit correlations and material characterization techniques.

Feedforward control of thermal history in laser powder bed fusion: Toward physics-based optimization of processing parameters

We developed and applied a model-driven feedforward control approach to mitigate thermal-induced flaw formation in laser powder bed fusion (LPBF) additive manufacturing process. The key idea was to avert heat buildup in a LPBF part before it is printed by adapting process parameters layer-by-layer based on insights from a physics-based thermal simulation model. The motivation being to replace cumbersome empirical build-and-test parameter optimization with a physics-guided strategy. The approach consisted of three steps: prediction, analysis, and correction. First, the temperature distribution of a part was predicted rapidly using a graph theory-based computational thermal model. Second, the model-derived thermal trends were analyzed to isolate layers of potential heat buildup. Third, heat buildup in affected layers was corrected before printing by adjusting process parameters optimized through iterative simulations. The effectiveness of the approach was demonstrated experimentally on two separate build plates. In the first build plate, termed fixed processing, ten different nickel alloy 718 parts were produced under constant processing conditions. On a second identical build plate, called controlled processing, the laser power and dwell time for each part was adjusted before printing based on thermal simulations to avoid heat buildup. To validate the thermal model predictions, the surface temperature of each part was tracked with a calibrated infrared thermal camera. Post-process the parts were examined with non-destructive and destructive materials characterization techniques. Compared to fixed processing, parts produced under controlled processing showed superior geometric accuracy and resolution, finer grain size, increased microhardness, and reduced surface roughness.

A practical procedure for vehicle sound package design using statistical energy analysis

Vehicle sound package has a substantial role in attenuation of vehicle noise for the purpose of improving interior comfort and reducing environmental noise pollution. In this paper, two approaches of absorptive design and multi-layer design are investigated to improve the performance of a sound package in automotive applications. For this purpose, the sound package of the engine compartment including hoodliner and dash insulator is studied. Furthermore, this paper proposes an experimentally validated prediction model through Statistical Energy Analysis (SEA) to evaluate the sound insulation of a vehicle body sound package. For this purpose, the research includes characterization techniques of sound package materials to determine intrinsic parameters of different layers required to develop a reliable SEA model. The inverse method and time-temperature superposition principle (TTSP) are utilized to characterize porous materials and heavy layer properties, respectively. The comparison of results that are experimentally obtained by acoustic cabin shows a fairly well agreement with the proposed SEA modeling procedure for the desired frequency range. By observing the results of the simulation for the hoodliner and dash insulator, it was revealed that the absorptive design combines the benefits of high sound absorption capability, wide absorption frequency band, and lightweight. Indeed, with an appropriate combination of layers, the multi-layer design can simultaneously provide a mixture of absorptive design attributes and sound insulation capabilities. The transmission loss obtained from the proposed design of the dash insulator revealed an increase by 42% without any reduction in the amount of sound absorption. Also, the sound absorption of the proposed hoodliner is enhanced more than twice in reference to the base design.

Investigation of microstructures, defects, and mechanical properties of titanium-zirconium-molybdenum alloy manufactured by wire arc additive manufacturing

Titanium‑zirconium‑molybdenum (TZM), one of the refractory alloys, has extraordinary physicochemical properties, making it ideal for usage in extreme environmental applications (e.g., high-temperature and nuclear). Due to the scalability and near-net shape fabrication, metal additive manufacturing processes have several advantages, leading it to be the possible solution for the fabrication of refractory alloy structures. Wire arc additive manufacturing (WAAM) has several advantages, including high deposition rate, energy efficiency, and cost-effective manufacturing of large components. In this study, we comprehensively investigated the relationships among process, microstructures, mechanical properties, and defects of TZM thin-walls manufactured by WAAM using four heat input conditions: 180A, 200A, 220A, and 240A. The microstructures were investigated using multi-scale material characterization techniques. Columnar grains were generated along the build direction, and carbide precipitates were found uniformly distributed in the Mo matrix. Multi-scale pores and cracks were present in the microstructures. The average microhardness values for the deposits ranged from 188.5 to 193.5 hardness scales of Vickers. The highest yield strength, 195 MPa, was found in the 200A heat input condition. The primary fracture mode was identified as a brittle transgranular. The area fraction of porosity was calculated >1% in each condition, with the largest being 2.04% in the 240A deposit.

Influence of annealing conditions on the performance of sputtered grown CZTS thin film solar cells

Kesterite Cu2ZnSnS4 (CZTS), with direct and tunable bandgap, high absorption coefficient, low-cost processing, earth-abundance, and non-toxicity, has become a promising absorber material for emerging thin film solar cells. The film growth, phase formation, and stoichiometry, as well as the electrical and optical properties of the sputtered grown CZTS thin films, are greatly influenced by the annealing temperature and pressure. In this work, we use a series of material characterization techniques followed by numerical simulations to determine how the annealing conditions affect the properties of CZTS thin films and the photovoltaic performance of the corresponding thin film solar cells. Sputtered grown CZTS samples were annealed at different temperatures (470 and 560 °C) and pressures (250 and 350 Torr). UV-visible spectroscopy was used to determine the optical bandgap and the absorption spectra. The experimentally determined values are then used as input parameters in the Solar Cell Capacitance Simulator-1 Dimension (SCAPS-1D) simulator tool to determine the solar cell performance. Simulation results show a maximum theoretical power conversion efficiency for the CZTS sample annealed at 560 °C and 350 Torr pressure. The results can lead to the optimization of sputtering conditions for obtaining high quality CZTS films that can yield excellent solar cell performance.

Machine-Learning Spectral Indicators of Topology.

Topological materials discovery has emerged as an important frontier in condensed matter physics. While theoretical classification frameworks have been used to identify thousands of candidate topological materials, experimental determination of materials' topology often poses significant technical challenges. X-ray absorption spectroscopy (XAS) is a widely used materials characterization technique sensitive to atoms' local symmetry and chemical bonding, which are intimately linked to band topology by the theory of topological quantum chemistry (TQC). Moreover, as a local structural probe, XAS is known to have high quantitative agreement between experiment and calculation, suggesting that insights from computational spectra can effectively inform experiments. In this work, computed X-ray absorption near-edge structure (XANES) spectra of more than 10000 inorganic materials to train a neural network (NN) classifier that predicts topological class directly from XANES signatures, achieving F1 scores of 89% and 93% for topological and trivial classes, respectively is leveraged. Given the simplicity of the XAS setup and its compatibility with multimodal sample environments, the proposed machine-learning-augmented XAS topological indicator has the potential to discover broader categories of topological materials, such as non-cleavable compounds and amorphous materials, and may further inform field-driven phenomena in situ, such as magnetic field-driven topological phasetransitions.

The mechanism and sorption kinetic analysis of hydrogen storage at room temperature using acid functionalized carbon nanotubes

The present work investigates the effect of acid functionalization of multiwalled carbon nanotubes (MWCNTs) on the physisorption based mechanism of hydrogen storage at room temperature. For this purpose, a suite of functionalized CNT samples is synthesized and subjected to a comprehensive range of material characterization techniques and hydrogen storage measurements. Nitric acid (HNO3) and the mixture of sulphuric acid and nitric acid (H2SO4:HNO3) are used for the synthesis at oxidation temperatures of 80 °C and 100 °C. Electron microscopy and X-ray photoelectron spectroscopy results reveal that acid functionalization causes major alternation in the physicochemical properties of the CNTs due to the varied concentration of oxygen functional groups. Particularly, the H2SO4:HNO3 functionalized sample at 100 °C is found to have the highest interlayer spacing, oxygen to carbon ratio (26.09 at. %), defect content, and specific surface area (215.3 m2/g). These features collectively contribute to substantially improved hydrogen storage properties, including a ∼150% increase in the hydrogen storage capacity at 298 K and 50 bar. Furthermore, kinetic analysis shows that the desorption follows a multiple diffusion process which is sensitive to the oxygen functional groups and structural defects, hence reducing the rate of desorption; whereas the adsorption is controlled by a more rapid, three-dimensional diffusion process.

Electron diffraction characterization of nanocrystalline materials using a Rietveld-based approach. Part II. Application to microstructural analysis

This is the second in a two-paper series concerning the quantitative characterization of nanocrystalline materials using an electron-diffraction-based approach, in which a full-pattern fitting Rietveld-based refinement is applied to electron powder diffraction data in transmission electron microscopy (TEM). Part I [Sinha et al. (2022). J. Appl. Cryst. 55, 953–965] established a standard calibration protocol to determine the instrumental effects, with special emphasis on the camera length and the diameter of the selected area apertures. Possible application cases are now considered to demonstrate the capabilities of the approach, including the evaluation of the phase composition of TEM specimens, an operation that reveals new application fields for this powerful materials characterization technique. In this regard, different types of material specimen are examined: nanocrystalline yttrium oxide, silicon, titanium dioxide and debris from disc brake wear, each one featuring specific aspects to be tackled with the proposed methodology. To demonstrate the limits of the proposed approach as concerns the material characteristics, an analysis of a hematite sample obtained from the heat treatment of natural goethite, displaying a relatively coarse crystallite size, is performed and a critical discussion of the results is given.

Modelling the extraction process parameters of amorphous silica-rich rice husk ash using hybrid RSM−BPANN−MOGA optimization technique

This study was aimed to optimize process conditions for recovery of amorphous silica-rich rice husk ash (RHA) as a highly reactive precursor of silicon compounds for valorization of a non-conventional agricultural waste rice husk. The optimization was accomplished using a hybrid multi-objective genetic algorithm (MOGA) coupled with back-propagation artificial neural networks (BPANN) and response surface methodology (RSM). Herein, process conditions, namely leaching temperature (65–85 °C) & time (0.5–1.5 h) and calcination temperature (450–650 °C) & time (1−3 h) were considered as independent variables. The influence of process parameters on % crystallinity and volume % of silica in RHA were studied based on X-ray diffraction analysis and RHA recovery. In the hybrid RSM−BPANN−MOGA model, predicted data of BPANN were used as initial score and regression equations of RSM were used for development of fitness function. A set of optimal solutions were obtained as Pareto front and the final optimum design point was selected using TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) decision-making tool. The optimized process conditions were: leaching temperature: 75 °C, leaching time: 1 h, calcination temperature: 550 °C, and calcination time: 2 h. The optimized model was validated with observed results and found to be a well-fitted with absolute errors of 7.42%, 2.03%, and 4.26% for % crystallinity, RHA recovery, and vol% of silica, respectively. Further, a comparative study was performed between non-leached RHA and optimized RHA using several material characterization techniques. This study showed relative superiority of optimized treatment parameters with increased purity and decreased crystallinity and porous particle morphology.

In Situ Optical Detection for Ultrasonic Characterization of Materials in a Mach 10 Hypersonic Wind Tunnel

We present results of in situ optical detection of ultrasonic waves generated in stainless steel and graphite samples mounted in a flat plate model during hypersonic flow in the 31-Inch Mach 10 wind tunnel at NASA Langley Research Center. Longitudinal waves are excited in the stainless steel and graphite sample inserts by using a contact piezoelectric transducer and the normal displacement on the surface of the sample, exposed to hypersonic fluid flow, is measured optically using a Sagnac interferometer. Measurements are consistent at different Reynolds numbers both with and without a turbulent trip strip present. Additionally, optical detection of laser-generated surface acoustic waves in a stainless-steel sample during flow is presented. These results are a demonstration of laser-based ultrasonics as an in situ material characterization technique in hypersonic flow, enabling potential applications of in situ monitoring of defect initialization and morphology in hypersonic environments.

Cu2ZnSnS4/MoS2/CNT- ternary heterostructures for paracetamol determination

Paracetamol (PAR) as a promising medicine being frequently used as pain reliever and in treatment of fever nonetheless may result in liver problems on excessive use. To counter this, here we have reported a novel electrochemical sensor utilizing hybrid nanocomposites of CZTS/MoS2/CNT. Ternary hydrothermal method is followed to develop a functionalized matrix of CZTS/MoS2 over the surface of carbon nanotube (CNT) network. Fast electrochemical sensors with excellent conductivity and chemical durability are constructed using carbon nanotubes. Material characterization techniques, X-Ray Diffraction spectroscopy (XRD), scanning and tunnelling electron microscopies (SEM and TEM) and energy dispersive X-ray spectroscopies is being employed to analyse as synthesized CZTS/MoS2/CNT. The electrochemical sensor is constructed by pasting an adequate amount of slurry composed CZTS/MoS2/CNT composite over a carbon paste electrode (CPE) functioning as working electrode. With the help of this investigation, the problematic identification of paracetamol from biological entities, such as blood, stomach, small intestine or gastro intestinal tract, has been overcome. Probably for the first-time, turnery CZTS/MoS2/CNT sensor is studied to sense PAR electrochemically. The sensitivity of PAR, identical to a promising sensitivity of 16 μA at 10 ppm paracetamol is achieved. The work clearly demonstrates the electrochemical sensing properties of ternary CZTS/MoS2/CNT towards PAR.

A modified sideband peak count based nonlinear ultrasonic technique for material characterization

The ultrasonic Non-Destructive Testing and Evaluation (NDT&E) has been widely used for Structural Health Monitoring (SHM). The conventional linear ultrasonic technique which is suitable for detecting macro-scale defects is routinely used in industry; however, it often fails to detect the micro-scale defects. Generally, micro-defects in a material appear first due to dislocations at grain boundaries. These micro-defects then grow and coalesce to form macro-defects. The crack growth rate is much faster for macro-defects than micro-defects. Therefore, monitoring micro-defects is important to avoid catastrophic failures of structures. Nonlinear ultrasonic techniques help to detect micro-defects. A recently developed nonlinear ultrasonic technique called Sideband Peak Count - Index (SPC-I) technique has some inherent advantages over other nonlinear techniques for monitoring progression of micro-defects. In this research, the SPC-I technique is further modified. This modified technique, Sideband Peak Intensity (SPI) technique, is shown to be more robust and easier to implement. Both SPC-I and SPI techniques are used to monitor the damage progression in impact induced damages in metals. Similarities and dissimilarities between these two techniques are investigated. Then it is concluded that the SPI technique is good as a general-purpose robust damage monitoring tool that can be used by less skilled users while the SPC-I technique although requires more skills has more sensitivity and has the flexibility for an in-depth damage analysis in materials.

Analysis of the thermal stability of residual stresses induced in Ti-6Al-4 V by high density LSP treatments

Laser Shock Processing (LSP) is increasingly applied as an effective technology for the improvement mechanical and surface properties of metallic materials for different types of components, mostly as a means of enhancement of their fatigue life behavior. As reported in previous contributions, a main effect resulting from the application of the LSP technique consists in the generation of relatively deep compression residual stresses fields allowing an improved mechanical behavior. In this paper, the special case of Ti-6Al-4 V alloy is considered with specific consideration of the microstructural changes and residual stresses fields justifying those macroscopic effects. In particular, the effect of the application of different typical LSP intensities on the microstructure and residual stresses fields introduced in this material and their possible correlation to the associated surface effects are analyzed. Emphasis is placed on the study of the thermal stability of these fields after an aging heat treatment at typical high temperature working conditions. The results show that, according to expectations, a certain level of residual stresses and dislocation density remains after in-work thermal aging. The combination of different material characterization techniques has made possible to obtain a correlated set of results highlighting the complementarity of different scale approaches from surface (X-ray) to bulk (neutrons) methods. A model based on the evolution of immobile dislocation density is proposed to rationalize the distribution of dislocation densities, pointing out that plastic deformation is retained. The results clearly show such material improvement stability under typical heavy-duty conditions, thus endorsing the use of the LSP for Ti-6Al-4 V as a suitable technology for industrial applications in relatively high temperature conditions.

Quantifying antisite defect concentrations in yttrium aluminum garnet by high-precision density analysis

Quantifying the nature and density of lattice defects in high-quality crystals is often difficult or impossible with commonly employed material characterization techniques. In many cases, even the density of intentionally doped impurities present in a grown crystal must be inferred indirectly using methods such as mapping spatial variations in crystal properties or, when the defects are optically active, interpreting optical absorption with imprecisely known oscillator strengths. In this work we explore gravimetric techniques to obtain absolute defect densities in crystals, a powerful approach often overlooked in modern materials science. A hydrostatic weighing apparatus based on Archimedes’ principle was constructed, tested, and refined to enable high-precision density measurements of small crystal samples. Application of this system is illustrated by determining the density of Yttrium Aluminum Garnet (YAG) relative to a high-purity silicon crystal density reference, minimizing traditional difficulties in correcting for the variations in surface tension and the water and air density due to small changes in ambient temperature, pressure, and solution composition. This method, using a relatively simple apparatus and small samples, is effective in measuring the intrinsic concentration of Y–Al antisite lattice defects in YAG, agreeing with results from far more elaborate high-resolution optical laser spectroscopy at cryogenic temperatures. Furthermore, we quantitatively analyze the effects of several potential sources for error, including natural variations in isotope distributions, residual surface contamination, and ambient temperature or pressure variations. Subsequently, we find that the density analysis method is a promising technique for characterizing new and modified materials being developed for applications ranging from solid-state lasers and scintillators to quantum information.

AuNP/Chitosan Nanocomposites Synthesized through Plasma Induced Liquid Chemistry and Their Applications in Photothermal Induced Bacteria Eradication.

In this work, a facile direct current atmospheric pressure micro-plasma (APM) technology was deployed for the synthesis of functional gold nanoparticle/chitosan (AuNP/CS) nanocomposites for the first time. Different experimental parameters, such as metal salt precursor concentration and chitosan viscosity, have been investigated to understand their effects on the resulting nanocomposite structures and properties. The nanocomposites were fully characterized using a wide range of material characterization techniques such as UV–vis, transmission electron microscope (TEM), Fourier transform infrared (FTIR) spectra and X-ray photoelectron spectroscopy (XPS) analyses. Potential reaction pathways have been proposed for the nanocomposite synthesis process. Finally, potential of the synthesized nanocomposites towards photothermal conversion and bacteria eradiation applications has been demonstrated. The results show that APM is a facile, rapid and versatile technique for the synthesis of AuNP/CS functional nanocomposites. Through this work, a more in-depth understanding of the multi-phase system (consisting of gas, plasma, liquid and solid) has been established and such understanding could shine a light on the future design and fabrication of new functional nanocomposites deploying the APM technique.